Estimating the changing burden of disease attributable to high fasting plasma glucose in South Africa for 2000, 2006 and 2012

Abstract


 
 
 
 Background. Worldwide, higher-than-optimal fasting plasma glucose (FPG) is among the leading modifiable risk factors associated with all- cause mortality and disability-adjusted life years (DALYs) due to the direct sequelae of diabetes and the increased risk for cardiovascular and chronic kidney disease.
 Objectives. To report deaths and DALYs of health outcomes attributable to high FPG by age and sex for South Africa (SA) for 2000, 2006 and 2012.
 Methods. Comparative risk assessment methodology was used to estimate the burden attributable to high FPG. A meta-regression analysis was performed using data from national and small-area studies to estimate the population distribution of FPG and diabetes prevalence. Attributable fractions were calculated for selected health outcomes and applied to local burden estimates from the second South African National Burden of Disease Study (SANBD2). Age-standardised rates were calculated using World Health Organization world standard population weights.
 Results. We estimated a 5% increase in mean FPG from 5.31 (95% confidence interval (CI) 5.18 - 5.43) mmol/L to 5.57 (95% CI 5.41 - 5.72) mmol/L and a 75% increase in diabetes prevalence from 7.3% (95% CI 6.7 - 8.3) to 12.8% (95% CI 11.9 - 14.0) between 2000 and 2012. The age-standardised attributable death rate increased from 153.7 (95% CI 126.9 - 192.7) per 100 000 population in 2000 to 203.5 (95% CI 172.2 - 240.8) per 100 000 population in 2012, i.e. a 32.4% increase. During the same period, age-standardised attributable DALY rates increased by 43.8%, from 3 000 (95% CI 2 564 - 3 602) per 100 000 population in 2000 to 4 312 (95% CI 3 798 - 4 916) per 100 000 population in 2012. In each year, females had similar attributable death rates to males but higher DALY rates. A notable exception was tuberculosis, with an age-standardised attributable death rate in males double that in females in 2000 (14.3 v. 7.0 per 100 000 population) and 2.2 times higher in 2012 (18.4 v. 8.5 per 100 000 population). Similarly, attributable DALY rates were higher in males, 1.7 times higher in 2000 (323 v. 186 per 100 000 population) and 1.6 times higher in 2012 (502 v. 321 per 100 000 population). Between 2000 and 2012, the age-standardised death rate for chronic kidney disease increased by 98.3% (from 11.7 to 23.1 per 100 000 population) and the DALY rate increased by 116.9% (from 266 to 578 per 100 000 population).
 Conclusion. High FPG is emerging as a public health crisis, with an attributable burden doubling between 2000 and 2012. The consequences are costly in terms of quality of life, ability to earn an income, and the economic and emotional burden on individuals and their families. Urgent action is needed to curb the increase and reduce the burden associated with this risk factor. National data on FPG distribution are scant, and efforts are warranted to ensure adequate monitoring of the effectiveness of the interventions.
 
 
 

Overview

“…[45] HIV communication programmes should continue to promote male circumcision and risk awareness in the context of non-marital relationships to prevent HIV transmission. [21] • SA included HPV vaccination for girls in Grade 4 in the national vaccination programme in 2014 [46] but needs to increase the coverage [47] and urgently review the cervical cancer screening and treatment programme in light of the WHO goal to eliminate cervical cancer by the year 2030. [48] 2 Interpersonal violence [33] • The age-standardised attributable death rates for interpersonal violence decreased from 100 to 71 per 100 000 population between 2000 and 2012.…”

“…To address these limitations, for the majority of risk factors (high systolic blood pressure, tobacco smoking, high fasting plasma glucose, alcohol use, high BMI, low fruit and vegetable intake, high LDL cholesterol, high sodium intake, iron deficiency) we adopted a meta-regression approach to the estimation of the parameters of the exposure distribution within each subgroup (age, sex and, for some risk factors, population group, province or urban/rural). [19][20][21][22][23][24][25][26][27] The modelling and estimation details varied across risk factorsdepending on the characteristics of the exposure and the available data -but in all cases the procedure involved two separate steps. In the first step, we used all available microdata and applied standard estimation methods (weighted estimators with robust standard error) to recover age, sex and survey-specific estimates of the parameters of interest (e.g.…”

“…[18] We used an externally estimated cross-walk equation to recover distributional parameters of fasting plasma glucose from the prevalence of diabetes, [15] and average blood concentration of haemoglobin in women of reproductive age from estimates referring to pregnant women only. [21]…”

“…The detailed evaluation of each risk factor and the quantification of the resultant attributable burden [19][20][21][22][23][24][25][26][27][31][32][33][34][35][36] revealed insights into trends. Key observations for each risk factor are summarised in Table 3.…”

“…High fasting plasma glucose [21] • There has been a 5% increase in mean fasting plasma glucose and a 75% increase in diabetes prevalence, resulting in an unacceptable 56% increase in attributable DALY rates between 2000 and 2012.…”