The avoidable disease burden associated with overweight and obesity in Kenya: A modelling study

Modelling the potential impact of a tax on fruit juice in South Africa: implications for the primary prevention of type 2 diabetes and health financing

BACKGROUND

South Africa is experiencing a persistent growth in non-communicable diseases. Diabetes is among the top ten causes of mortality, especially among women, which is partly driven by high levels of added sugar consumption and obesity. To reduce obesity rates and the incidence of diabetes, South Africa introduced a tax on sugar sweetened beverages (also known as the Health Promotion Levy (HPL)) in 2018. The tax is applicable to sugar-sweetened beverages but excludes 100% fruit juice. The government is currently considering extending the tax to include fruit juices. This study models the potential health and economic impact of taxing fruit juices at 20% of the retail price of one liter.

METHODS

To analyze the distributional impact of the tax, this study uses extended cost-effectiveness analysis methodology. Data on price elasticities, healthcare cost, income, fruit juice consumption were sourced from the literature and representative national surveys. The potential impact of the tax on diabetes incidence, prevalence, mortality, and financial benefits were estimated for each income group (lowest, quintile 1 to highest, quintile 5).

FINDINGS

We estimate that a 20% tax on fruit juice would avert 156,640 incident cases of type 2 diabetes mellitus over 20 years, with most disease averted occurring among the first- and fifth-income groups. Averted deaths from diabetes would average 2,000 deaths per quintile (for quintiles 1 to 4) and about 2,800 in quintile 5. The improved health resulting from averted incidence and deaths will reduce overall healthcare expenditure by R7.5 billion over 20 years, of which R2.3 billion will occur in the fifth quintile. The South African government will also save about R300 million in subsidizing diabetes-related healthcare cost as a result of prevention; and would raise R8.6 billion in tax revenues per annum. Out-of-pocket expenditure savings will be R303 million and a financial risk protection (money-metric value of insurance) of R4.6 billion over the 20-year period.

CONCLUSION

We conclude that an HPL that significantly raises the retail price of fruit juices would reduce consumption and diabetes-related morbidity and mortality. The tax will also provide significant financial benefits in the form of reduced healthcare costs for both government and households as well as providing financial risk protection to individuals. Health taxes are win-win policies that improve population health and generate revenue for governments to fund public health services delivery and thus improve overall health financing activities of the government. Therefore, population level disease prevention measures such as health taxes are important for achieving universal health coverage.

Health gains from achieving optimal body mass index in Australia: a simulation study

Background

We estimated the health gains and health inequality impacts for the Australian population alive in 2021 (n = 25.0 million) in the next 20 years and over their remaining lifespan, from shifting everyone above a BMI of 25 kg/m2 to 25 kg/m2 compared to the BMI distribution in 2021 persisting into the future.

Methods

National Health Survey 2017-2018 was used to estimate BMI distributions by sex, age and, socio-economic status (Socio-Economic Indexes for Areas; SEIFA). A proportional multistate life table linking BMI to 19 associated diseases and allowing for time lags and competing morbidity and mortality, was used to estimate the future stream of health adjusted life years (HALYs) gained from eradicating high BMI.

Findings

Undiscounted health gains in the first 20 years and lifetime of the population were, respectively, 2.00 million (95% uncertainty interval 1.70-2.32) and 20.4 million (17.0-24.2) (at a 3% annual discount rate, HALY gains were 1.37 and 5.77 million, respectively). Reductions in the incidence of cardio metabolic diseases contributed 61% (95% UI: 54%-68%) of the undiscounted health gains in the first 20 years, musculoskeletal diseases contributed 26% (20%-32%) and cancer 5% (3%-8%). HALY gains in the first 20 years and lifetime, per person alive in 2021, were 2.5 (2.4-2.5) and 1.9 (1.9-2.0) times higher for the most compared to the least deprived SEIFA quintile.

Interpretation

The total theoretical envelope of health gains, and health inequality reductions, through eradication of BMI is substantial. Our modeling infrastructure can be used to estimate the health impacts and cost effectiveness of many actual interventions.

Funding

No funding was received for the study.

Potential health and economic impact of achieving Kenya's overweight and obesity reduction target: a modelling study

Introduction

Kenya has adopted the WHO target of halting the rise of overweight, including obesity, by 2025. This paper assesses the potential impact of achieving the set target on health, healthcare cost and productivity.

Methods

We used a proportional multistate life table model (Kenya Obesity Model) to simulate the 2019 population of Kenya over their lifetime. We compared a scenario in which body mass index (BMI) distributions stabilise in 2025 against one whose BMI distributions stabilise in 2044, and quantified changes in disease-specific health outcomes, healthcare costs and productivity. We searched the literature to identify the best estimates of the total and disease-specific healthcare costs in Kenya. We used the Human Capital Approach to estimate productivity gains.

Results

If BMI distributions stabilised in 2025, an estimated 6.8 million health-adjusted life years (HALYs) (95% uncertainty interval (UI) 5.8-7.9 million) would be saved over the lifetime of the 2019 Kenyan population (135 HALYs per 1000 persons). A total of US$755 million in body mass-related healthcare costs could be saved by 2044 (US$15 per capita). For context, this equates to 16% of Kenya's annual healthcare expenditure. Over the lifetime, ~US$3 billion healthcare costs could be saved (US$62 per capita). By 2044, the total productivity gain resulting from a reduction in high BMI-related mortality and morbidity (combined) was ~US$5.8 billion (~US$237 per capita).

Conclusion

Achieving Kenya's overweight and obesity reduction target could improve health outcomes and also yield substantial healthcare cost savings and productivity gains.

The health and economic impact and cost effectiveness of interventions for the prevention and control of overweight and obesity in Kenya: a stakeholder engaged modelling study

BACKGROUND

The global increase in mean body mass index has resulted in a substantial increase of non-communicable diseases (NCDs), including in many low- and middle-income countries such as Kenya. This paper assesses four interventions for the prevention and control of overweight and obesity in Kenya to determine their potential health and economic impact and cost effectiveness.

METHODS

We reviewed the literature to identify evidence of effect, determine the intervention costs, disease costs and total healthcare costs. We used a proportional multistate life table model to quantify the potential impacts on health conditions and healthcare costs, modelling the 2019 Kenya population over their remaining lifetime. Considering a health system perspective, two interventions were assessed for cost-effectiveness. In addition, we used the Human Capital Approach to estimate productivity gains.

RESULTS

Over the lifetime of the 2019 population, impacts were estimated at 203,266 health-adjusted life years (HALYs) (95% uncertainty interval [UI] 163,752 - 249,621) for a 20% tax on sugar-sweetened beverages, 151,718 HALYs (95% UI 55,257 - 250,412) for mandatory kilojoule menu labelling, 3.7 million HALYs (95% UI 2,661,365-4,789,915) for a change in consumption levels related to supermarket food purchase patterns and 13.1 million HALYs (95% UI 11,404,317 - 15,152,341) for a change in national consumption back to the 1975 average levels of energy intake. This translates to 4, 3, 73 and 261 HALYs per 1,000 persons. Lifetime healthcare cost savings were approximately United States Dollar (USD) 0.14 billion (USD 3 per capita), USD 0.08 billion (USD 2 per capita), USD 1.9 billion (USD 38 per capita) and USD 6.2 billion (USD 124 per capita), respectively. Lifetime productivity gains were approximately USD 1.8 billion, USD 1.2 billion, USD 28 billion and USD 92 billion. Both the 20% tax on sugar sweetened beverages and the mandatory kilojoule menu labelling were assessed for cost effectiveness and found dominant (health promoting and cost-saving).

CONCLUSION

All interventions evaluated yielded substantive health gains and economic benefits and should be considered for implementation in Kenya.

Double burden of malnutrition and its associated factors among women in low and middle income countries: findings from 52 nationally representative data

BACKGROUND

Double burden of malnutrition (DBM) is an emerging global public health problem. The United Nations member states adopted eradicating all forms of malnutrition as an integral component of the global agenda. However, there is evidence of a high burden of undernutrition among women and rising rates of overweight and obesity, especially in low and middle income countries (LMICs). Therefore, this study aimed to investigate the prevalence and associated factors of underweight, overweight, and obesity among women of reproductive age in LMICs.

METHODS

Data for the study were drawn from a recent 52 Demographic and Health Surveys (DHS) conducted in LMICS. We included a sample of 1,099,187 women of reproductive age. A multilevel multinomial logistic regression model was used to identify factors associated with DBM. Adjusted relative risk ratio (RRR) with a 95% Confidence Interval (CI) was reported to show an association.

RESULTS

The prevalence of underweight, overweight, and obesity in LMICs among women of reproductive age was 15.2% (95% CI: 15.1-15.3), 19.0% (95% CI: 18.9- 19.1), and 9.1% (95% CI: 9.0-9.2), respectively. This study found that women aged 24-34 years, aged ≥ 35 years, with primary, secondary, and above educational level, from wealthy households, using modern contraceptives, exposed to media (radio and television), and with high parity (more than one birth) were more likely to have overweight and obesity and less likely to have underweight. Moreover, the risk of having obesity (RRR = 0.59; 95% CI = 0.58-0.60 and overweight (RRR = 0.78; 95% CI = 0.77-0.79) were lower among rural women, while the risk of being underweight was (RRR = 1.13; 95% CI = 1.11-1.15) higher among rural women compared to urban women.

CONCLUSION

The prevalence of underweight, overweight, and obesity was high among women of reproductive age in LMICs. Underweight, overweight, and obesity are influenced by sociodemographic, socioeconomic, and behavioral-related factors. This study shows that, in order to achieve Sustainable Development Goal 2, a multifaceted intervention approach should be considered to prevent both forms of malnutrition in women of reproductive age. This can be achieved by raising awareness and promoting healthy behaviors such as healthy eating and physical activity, especially among educated women, women from wealthy households, and women exposed to the media.

Food Knowledge for Better Nutrition and Health: A Study among University Students in Portugal

When students enter university, they suffer adaptations, including, usually, greater autonomy and responsibility for the choices they make. Therefore, it is crucial that they are well informed so as to make healthier food choices. The aim of this study was to determine whether sociodemographic characteristics, academic performance and lifestyle (tobacco and alcohol consumption) interfere with food literacy in university students. A quantitative, analytical, descriptive, transversal and correlational study was carried out, using quantitative data obtained through a questionnaire survey applied to a sample of 924 university students in Portugal. Food literacy was assessed through a scale of 27 items, distributed in three dimensions: D1-Literacy about food nutritional value and composition, D2-Literacy about labelling and food choice and D3-Literacy about healthy eating practices. Results showed no differences in food literacy according to sex or age. However, food literacy varied significantly with nationality, either globally (p = 0.006) or in the different dimensions evaluated (p-values of 0.005, 0.027 and 0.012 for D1, D2 and D3, respectively). In terms of academic achievement, the results showed no significant differences according to self-reported academic performance or even to the average classification obtained in the course. Regarding lifestyle variables, it was observed that alcohol consumption or smoking are not associated with food literacy, that is, food literacy does not vary significantly with these two lifestyle variables. In conclusion, food literacy in general and the dimensions evaluated are essentially constant among university students in Portugal, only varying for students from abroad. These results help to better perceive the food literacy levels for the population under study, university students, and that can be a valuable tool to better increase food literacy at these institutions as a way to better prepare for a healthier life and proper food habits that can enhance health in the long term.

The most effective exercise to prevent obesity: A longitudinal study of 33,731 Taiwan biobank participants

Regular physical exercise is recommended to reduce the risk of obesity. However, it remains unclear which activities are more effective in preventing obesity. In this study, five obesity indices and lifestyle factors of 33,731 Taiwan Biobank adults were measured/collected twice with a mean time interval of 4.06 years. A linear mixed effects model was fitted to assess the associations of exercises with obesity indices, in which a random intercept term was used to account for individual differences. The five obesity indices included body mass index (BMI), body fat percentage (BFP), waist circumference (WC), hip circumference (HC), and waist-hip ratio (WHR). Among 23 exercises, jogging and yoga were consistently the most effective choices across all five obesity indices. One more weekly hour to jog was associated with a 0.093 kg/m2 decrease in BMI (p = 4.2E-20), a 0.297% decrease in BFP (p = 3.8E-36), a 0.398 cm decrease in WC (p = 1.6E-21), and a 2.9E-3 decrease in WHR (p = 1.3E-17). One more weekly hour to perform yoga was associated with a 0.225 cm decrease in HC (p = 6.4E-14). Jogging is an exercise for the entire body. Arms swing, waist turn, legs and feet run, and shoulders and abdomen are also involved in this act. By contrast, many yoga poses use muscles around the hips and pelvis, and therefore yoga is the most effective exercise to reduce HC.