Patterns of tobacco use in low and middle income countries by tobacco product and sociodemographic characteristics: nationally representative survey data from 82 countries.

OBJECTIVES: To determine the prevalence and frequency of using any tobacco product and each of a detailed set of tobacco products, how tobacco use and frequency of use vary across countries, world regions, and World Bank country income groups, and the socioeconomic and demographic gradients of tobacco use and frequency of use within countries. DESIGN: Secondary analysis of nationally representative, cross-sectional, household survey data from 82 low and middle income countries collected between 1 January 2015 and 31 December 2020. SETTING: Population based survey data. PARTICIPANTS: 1 231 068 individuals aged 15 years and older. MAIN OUTCOME MEASURES: Self-reported current smoking, current daily smoking, current smokeless tobacco use, current daily smokeless tobacco use, pack years, and current use and use frequencies of each tobacco product. Products were any type of cigarette, manufactured cigarette, hand rolled cigarette, water pipe, cigar, oral snuff, nasal snuff, chewing tobacco, and betel nut (with and without tobacco). RESULTS: The smoking prevalence in the study sample was 16.5% (95% confidence interval 16.1% to 16.9%) and ranged from 1.1% (0.9% to 1.3%) in Ghana to 50.6% (45.2% to 56.1%) in Kiribati. The user prevalence of smokeless tobacco was 7.7% (7.5% to 8.0%) and prevalence was highest in Papua New Guinea (daily user prevalence of 65.4% (63.3% to 67.5%)). Although variation was wide between countries and by tobacco product, for many low and middle income countries, the highest prevalence and cigarette smoking frequency was reported in men, those with lower education, less household wealth, living in rural areas, and higher age. CONCLUSIONS: Both smoked and smokeless tobacco use and frequency of use vary widely across tobacco products in low and middle income countries. This study can inform the design and targeting of efforts to reduce tobacco use in low and middle income countries and serve as a benchmark for monitoring progress towards national and international goals.

Targeting Hypertension Screening in Low- and Middle-Income Countries: A Cross-Sectional Analysis of 1.2 Million Adults in 56 Countries.

Background As screening programs in low- and middle-income countries (LMICs) often do not have the resources to screen the entire population, there is frequently a need to target such efforts to easily identifiable priority groups. This study aimed to determine (1) how hypertension prevalence in LMICs varies by age, sex, body mass index, and smoking status, and (2) the ability of different combinations of these variables to accurately predict hypertension. Methods and Results We analyzed individual-level, nationally representative data from 1 170 629 participants in 56 LMICs, of whom 220 636 (18.8%) had hypertension. Hypertension was defined as systolic blood pressure ≥140 mm Hg, diastolic blood pressure ≥90 mm Hg, or reporting to be taking blood pressure-lowering medication. The shape of the positive association of hypertension with age and body mass index varied across world regions. We used logistic regression and random forest models to compute the area under the receiver operating characteristic curve in each country for different combinations of age, body mass index, sex, and smoking status. The area under the receiver operating characteristic curve for the model with all 4 predictors ranged from 0.64 to 0.85 between countries, with a country-level mean of 0.76 across LMICs globally. The mean absolute increase in the area under the receiver operating characteristic curve from the model including only age to the model including all 4 predictors was 0.05. Conclusions Adding body mass index, sex, and smoking status to age led to only a minor increase in the ability to distinguish between adults with and without hypertension compared with using age alone. Hypertension screening programs in LMICs could use age as the primary variable to target their efforts.

Variation in the Proportion of Adults in Need of Blood Pressure-Lowering Medications by Hypertension Care Guideline in Low- and Middle-Income Countries: A Cross-Sectional Study of 1 037 215 Individuals From 50 Nationally Representative Surveys.

BACKGROUND: Current hypertension guidelines vary substantially in their definition of who should be offered blood pressure-lowering medications. Understanding the effect of guideline choice on the proportion of adults who require treatment is crucial for planning and scaling up hypertension care in low- and middle-income countries. METHODS: We extracted cross-sectional data on age, sex, blood pressure, hypertension treatment and diagnosis status, smoking, and body mass index for adults 30 to 70 years of age from nationally representative surveys in 50 low- and middle-income countries (N = 1 037 215). We aimed to determine the effect of hypertension guideline choice on the proportion of adults in need of blood pressure-lowering medications. We considered 4 hypertension guidelines: the 2017 American College of Cardiology/American Heart Association guideline, the commonly used 140/90 mm Hg threshold, the 2016 World Health Organization HEARTS guideline, and the 2019 UK National Institute for Health and Care Excellence guideline. RESULTS: The proportion of adults in need of blood pressure-lowering medications was highest under the American College of Cardiology/American Heart Association, followed by the 140/90 mm Hg, National Institute for Health and Care Excellence, and World Health Organization guidelines (American College of Cardiology/American Heart Association: women, 27.7% [95% CI, 27.2-28.2], men, 35.0% [95% CI, 34.4-35.7]; 140/90 mm Hg: women, 26.1% [95% CI, 25.5-26.6], men, 31.2% [95% CI, 30.6-31.9]; National Institute for Health and Care Excellence: women, 11.8% [95% CI, 11.4-12.1], men, 15.7% [95% CI, 15.3-16.2]; World Health Organization: women, 9.2% [95% CI, 8.9-9.5], men, 11.0% [95% CI, 10.6-11.4]). Individuals who were unaware that they have hypertension were the primary contributor to differences in the proportion needing treatment under different guideline criteria. Differences in the proportion needing blood pressure-lowering medications were largest in the oldest (65-69 years) age group (American College of Cardiology/American Heart Association: women, 60.2% [95% CI, 58.8-61.6], men, 70.1% [95% CI, 68.8-71.3]; World Health Organization: women, 20.1% [95% CI, 18.8-21.3], men, 24.1.0% [95% CI, 22.3-25.9]). For both women and men and across all guidelines, countries in the European and Eastern Mediterranean regions had the highest proportion of adults in need of blood pressure-lowering medicines, whereas the South and Central Americas had the lowest. CONCLUSIONS: There was substantial variation in the proportion of adults in need of blood pressure-lowering medications depending on which hypertension guideline was used. Given the great implications of this choice for health system capacity, policy makers will need to carefully consider which guideline they should adopt when scaling up hypertension care in their country.

The state of hypertension care in 44 low-income and middle-income countries: a cross-sectional study of nationally representative individual-level data from 1·1 million adults.

BACKGROUND: Evidence from nationally representative studies in low-income and middle-income countries (LMICs) on where in the hypertension care continuum patients are lost to care is sparse. This information, however, is essential for effective targeting of interventions by health services and monitoring progress in improving hypertension care. We aimed to determine the cascade of hypertension care in 44 LMICs-and its variation between countries and population groups-by dividing the progression in the care process, from need of care to successful treatment, into discrete stages and measuring the losses at each stage. METHODS: In this cross-sectional study, we pooled individual-level population-based data from 44 LMICs. We first searched for nationally representative datasets from the WHO Stepwise Approach to Surveillance (STEPS) from 2005 or later. If a STEPS dataset was not available for a LMIC (or we could not gain access to it), we conducted a systematic search for survey datasets; the inclusion criteria in these searches were that the survey was done in 2005 or later, was nationally representative for at least three 10-year age groups older than 15 years, included measured blood pressure data, and contained data on at least two hypertension care cascade steps. Hypertension was defined as a systolic blood pressure of at least 140 mm Hg, diastolic blood pressure of at least 90 mm Hg, or reported use of medication for hypertension. Among those with hypertension, we calculated the proportion of individuals who had ever had their blood pressure measured; had been diagnosed with hypertension; had been treated for hypertension; and had achieved control of their hypertension. We weighted countries proportionally to their population size when determining this hypertension care cascade at the global and regional level. We disaggregated the hypertension care cascade by age, sex, education, household wealth quintile, body-mass index, smoking status, country, and region. We used linear regression to predict, separately for each cascade step, a country's performance based on gross domestic product (GDP) per capita, allowing us to identify countries whose performance fell outside of the 95% prediction interval. FINDINGS: Our pooled dataset included 1 100 507 participants, of whom 192 441 (17·5%) had hypertension. Among those with hypertension, 73·6% of participants (95% CI 72·9-74·3) had ever had their blood pressure measured, 39·2% of participants (38·2-40·3) had been diagnosed with hypertension, 29·9% of participants (28·6-31·3) received treatment, and 10·3% of participants (9·6-11·0) achieved control of their hypertension. Countries in Latin America and the Caribbean generally achieved the best performance relative to their predicted performance based on GDP per capita, whereas countries in sub-Saharan Africa performed worst. Bangladesh, Brazil, Costa Rica, Ecuador, Kyrgyzstan, and Peru performed significantly better on all care cascade steps than predicted based on GDP per capita. Being a woman, older, more educated, wealthier, and not being a current smoker were all positively associated with attaining each of the four steps of the care cascade. INTERPRETATION: Our study provides important evidence for the design and targeting of health policies and service interventions for hypertension in LMICs. We show at what steps and for whom there are gaps in the hypertension care process in each of the 44 countries in our study. We also identified countries in each world region that perform better than expected from their economic development, which can direct policy makers to important policy lessons. Given the high disease burden caused by hypertension in LMICs, nationally representative hypertension care cascades, as constructed in this study, are an important measure of progress towards achieving universal health coverage. FUNDING: Harvard McLennan Family Fund, Alexander von Humboldt Foundation.

Burden of cumulative risk factors associated with non-communicable diseases among adults in Uganda: evidence from a national baseline survey.

BACKGROUND: Modification of known risk factors has been the most tested strategy for dealing with non-communicable diseases (NCDs). The cumulative number of NCD risk factors exhibited by an individual depicts a disease burden. However, understanding the risk factors associated with increased NCD burden has been constrained by scarcity of nationally representative data, especially in the developing countries and not well explored in the developed countries as well. METHODS: Assessment of key risk factors for NCDs using population data drawn from 3987 participants in a nationally representative baseline survey in Uganda was made. Five key risk factors considered for the indicator variable included: high frequency of tobacco smoking, less than five servings of fruit and vegetables per day, low physical activity levels, high body mass index and raised blood pressure. We developed a composite indicator dependent variable with counts of number of risk factors associated with NCDs per participant. A statistical modeling framework was developed and a multinomial logistic regression model was fitted. The endogenous and exogenous predictors of NCD cumulative risk factors were assessed. RESULTS: A novel model framework for cumulative number of NCD risk factors was developed. Most respondents, 38 · 6% exhibited one or two NCD risk factors each. Of the total sample, 56 · 4% had at least two risk factors whereas only 5.3% showed no risk factor at all. Body mass index, systolic blood pressure, diastolic blood pressure, consumption of fruit and vegetables, age, region, residence, type of residence and land tenure system were statistically significant predictors of number of NCD risk factors (p < 0 · 05). With exception to diastolic blood pressure, increase in age, body mass index, systolic blood pressure and reduction in daily fruit and vegetable servings were found to significantly increase the relative risks of exhibiting cumulative NCD risk factors. Compared to the urban residence status, the relative risk of living in a rural area significantly increased the risk of having 1 or 2 risk factors by a multiple of 1.55. CONCLUSIONS: The non-communicable disease burden is on the increase, with more participants reporting to have at least two risk factors. Our findings imply that, besides endogenous factors, exogenous factors such as region, residence status, land tenure system and behavioral characteristics have significant causal effects on the cumulative NCD risk factors. Subsequently, while developing interventions to combat cumulative risk factors of NCDs, the Ministry of Health needs to employ a more holistic approach to facilitate equitable health and sensitization across age, residence and regional divide.

Tobacco use and associated factors among Adults in Uganda: Findings from a nationwide survey.

BACKGROUND: Tobacco use and the exposure to tobacco smoke is one of the most preventable causes of death and disability globally. The risk is even higher among daily tobacco users. The World Health Organization (WHO) has recommended that surveillance of major risk factors for Non Communicable Diseases (NCDs) such as tobacco use is imperative to predict the future burden of NCDs, identify interventions to reduce future burden and monitor emerging patterns and trends. In 2014 the first Uganda nation-wide NCD risk factor survey was carried out to estimate the prevalence of major NCD risk factors. We analyzed data from this survey to estimate the prevalence of daily tobacco use and associated risk factors. METHODS: A nationally representative sample was drawn stratified by the four regions of the country. The WHO's STEPwise tool was used to collect data on demographic and behavioral characteristics including tobacco use, physical and biochemical measurements. Tobacco use was divided into three categories; daily tobacco use, daily smoked tobacco use and daily smokeless tobacco use. Weighted logistic regression analysis was used to identify factors associated with daily tobacco use. RESULTS: Of the 3983 participants, 9.2 % (366) were daily tobacco users, 7.4 % (294) were daily smoked tobacco users and 2.9 % (115) were daily smokeless tobacco users. Male participants were more likely to be daily tobacco users compared with female participants AOR 5.51 [3.81-7.95]. Compared with participants aged 18-29 years, those aged 30-49 years were more likely to be daily tobacco users AOR 2.47 [1.54-3.94] as were those aged 50-69 years AOR 2.82 [1.68-4.74]. Compared with participants without any education, those with primary education were less likely to be daily tobacco users AOR 0.43 [0.29-0.65], as were those with secondary education AOR 0.21 [0.14-0.33] and those with university level of education AOR 0.23 [0.11-0.48]. Compared with participants in the central region, those in the eastern region were more likely to be daily tobacco users AOR 2.14 [1.33-3.45] as were those in the northern region AOR 4.31 [2.79-6.45] and those in the western region AOR 1.87 [1.18-2.97]. Participants who were underweight were more likely to be daily tobacco users compared with people with normal BMI AOR 2.19 [1.48-3.24]. CONCLUSIONS: In agreement with previous surveys on tobacco use, there is a high prevalence of tobacco use in Uganda with almost 1 in every 10 Ugandans using tobacco products daily. Being older, male, having no formal education, residing in the east, north and western regions and having low BMI were significantly associated with daily tobacco use. This information provides a useful benchmark to the National Tobacco Control Program for the designing of public health interventions for the control and prevention of tobacco use in Uganda.

Diabetes Treatment as "Homework": Consequences for Household Knowledge and Health Practices in Rural Uganda.

BACKGROUND: Health professionals assign diabetes patients "homework" in that they give them instructions on how to manage diabetes, recognizing that most diabetes care takes place in the home setting. We studied how homework is practiced and whether knowledge and behavioral practices related to diabetes self-management diffuse from patients to their housemates. METHOD: This mixed-methods study combined quantitative data from a household survey including 90 rural Ugandan households (50% had a member with type 2 diabetes [T2D]) with qualitative data from health facilities and interviews with 10 patients with T2D. Focus for data collection was knowledge and practices related to diabetes homework. A generalized mixed model was used to analyze quantitative data, while content analysis was used for qualitative data analysis. RESULTS: Patients with T2D generally understood the diabetes homework assignments given by health professionals and carried out their homework with support from housemates. Although adherence to recommended diet was variable, housemates were likely to eat a healthier diet than if no patient with T2D lived in the household. Knowledge related to diabetes homework diffused from the patients to housemates and beyond to neighbors and family living elsewhere. Knowledge about primary prevention of T2D was almost absent among health staff, patients, and relatives. CONCLUSIONS: Homework practices related to T2D improve diabetes-related knowledge and may facilitate healthy eating in nondiabetic housemates. These findings suggest that having a chronic disease in the household provides an opportunity to improve health in the entire household and address the lack of knowledge about prevention of T2D.

A comparison of cardiometabolic risk factors in households in rural Uganda with and without a resident with type 2 diabetes, 2012-2013.

INTRODUCTION: Few studies have examined the health consequences of living in a household with a person who has been diagnosed with type 2 diabetes (T2D). We assessed the association of sharing a household with a person with diagnosed T2D and risk factors for cardio-metabolic diseases in Uganda, a low-income country. METHODS: Ninety households with 437 residents in southwestern Uganda were studied from December 2012 through March 2013. Forty-five of the households had a member with diagnosed T2D (hereafter "diabetic household"), and 45 households had no member with diagnosed T2D (hereafter "nondiabetic household"). We compared glycosylated hemoglobin (HbA1c), fasting plasma glucose (FPG), hypertension, anthropometry, aerobic capacity, physical activity, nutrition, smoking, and diabetes-related knowledge of people without diagnosed T2D living in diabetic and nondiabetic households. RESULTS: People living in diabetic households had a significantly higher level of diabetes-related knowledge, lower levels of FPG (5.6 mmol/L vs 6.0 mmol/L), and fewer smoked (1.3% vs 12.9%) than residents of nondiabetic households. HbA1c was significantly lower in people aged 30 years or younger (5.2% vs 5.4%) and in males (5.2% vs 5.4%) living in diabetic households compared to residents of nondiabetic households. No differences were found between the 2 types of households in overweight and obesity, upper-arm fat area, intake of staple foods or cooking oil, or physical activity. CONCLUSIONS: Sharing a household with a person with T2D may have unexpected benefits on the risk factor profile for cardio-metabolic diseases, probably because of improved health behaviors and a closer connection with the health care system. Thus, future studies should consider the household for interventions targeting primary and secondary prevention of T2D.