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The "first digit law" or "Benford's law" is a mathematical distribution discovered by Simon Newcomb and Frank Benford. It states, that the probability of the leading number d (d∈{1,…,9}) in many natural datasets follows: P (d)=log10 (d+1)-log10 (d)=log10 (1+1/d). It was successfully used through tax authorities and "forensic accounting" in order to detect fraud and other irregularities. Benfords law was almost neglected for its use outside financial accounting. The planning for health care systems in developing countries is extremely dependant on good, valid data. Whether you plan the catchment area for the future district hospitals, the number of health posts, the staff establishment for the central hospital or the drug budget in the Ministry. The "first digit law" can be used in medicine, public health, physiology and development aid to unmask questionable data, to discover unexpected challenges, difficulties in the data collection process, loss through corruption and criminal fraud. Our hypothesis suggests, that the "first digit law" is a cost effective tool, which is easy to use for most people in the medical profession, which does not really needs complicated statistical software and can be used on the spot, even in the resource restricted conditions of developing countries. Several preconditions (like the size of the data set and its reach over more than two dimensions) have to be fulfilled, but then Benfords law can be used by any clinician, physiologist, public health specialist or aid consultant without difficulties and without deeper statistical knowledge in the four steps, we suggest in this article. The consequences will be different depending on the level (local regional, national, continental, international) on which you will use the law. All levels will be enabled to get insight into the validity of the data-challenges for the other levels without the help of trained statisticians or accountants. We believe that the "first digit law" is a vastly underestimated and neglected, but extremely useful tool for the identification of unexpected challenges, supervision and control in various parts of medicine and public health for almost all aspects of development aid. [ABSTRACT FROM AUTHOR]

Dyslipidaemia is a significant risk factor for cardiovascular events but is often neglected in most resource-poor settings. We aimed to investigate the prevalence, biochemical characteristics, screening and management practice for dyslipidaemia among patients with DM, hypertension, and both DM and hypertension at a tertiary teaching hospital in Southern Malawi, Africa. A total of 256 adult participants (DM=100; hypertension =100; both condition = 56) were included in the cross-sectional study in 2021. Medical data and anthropometric measurements were recorded. Blood samples were analysed for HbA1C and serum lipids. Associated risk factors for dyslipidaemia were assessed. Dyslipidaemia was prevalent in 73.5%, 71.8%, and 76.7% of participants with DM, hypertension, and both conditions. High low-density lipoprotein cholesterol (LDL-C) was the most common dyslipidaemia type in all participant groups. Participants with both diabetes and hypertension had 2.4 times (95% CI 1.2 - 4.6) increased risk of LDL-C dyslipidaemia than those with diabetes alone (p=0.02). Overweight or obesity, and age over 30 years were risks for dyslipidaemia in patients with DM alone (RR 1.3 (95% CI 1.1 – 1.6), p=0.04, and RR 2.2 (95% CI 1.2 – 4.7) (p<0.01) respectively. Overweight and obesity predicted LDL-C dyslipidaemia in hypertensive patients (RR 3.492 (95% CI 1.234 - 9.884) p <0.001). Poorly controlled hypertension was associated with a 1.8 times risk (95% CI 1.06 – 2.7) of dyslipidaemia in patients with both DM and hypertension (p<0.01). Only 1% of the participants ever had a lipogram performed before the study and were on lipid-lowering therapy. Dyslipidaemia was highly prevalent, especially in individuals with both DM and hypertension. Screening and managing dyslipidaemia should be reinforced to reduce the risk of major cardiovascular events in this population at high risk. [ABSTRACT FROM AUTHOR]

Dyslipidaemia, obesity and vitamin D insufficiency are important risk factors for cardiovascular disease and may increase the risk for severe COVID-19 among individuals with Diabetes mellitus. To investigate the prevalence of dyslipidaemia, obesity and vitamin D insufficiency among patients attending the diabetes clinic at Queen Elizabeth Central Hospital in Blantyre, Malawi. A total of 102 participants were included in the cross-sectional study. Medical data were collected, and anthropometric measurements were performed. Blood samples were collected for HbA1C, serum lipogram and vitamin D analyses. Associated risk factors for dyslipidaemia and vitamin D insufficiency were assessed. A proportion of 74% of the participants had dyslipidaemia. Low-density lipoprotein-cholesterol dyslipidaemia was the most common form of dyslipidaemia (52%). Overweight and obesity was prevalent in 58% of the participants. The median (IQR) HBA1C level was 11% (9-14 %). Overweight or obesity and age over 30 years were risks for dyslipidaemia (RR 1.3 (95% CI 1.1 – 1.6), p=0.04, and RR 2.2 (95% CI 1.2 – 4.7) p=0.003, respectively. The prevalence of vitamin D insufficiency in the study group was 76%. HBA1C of > 7% was positively associated with vitamin D insufficiency (RR 1.6 (CI 1.0 – 2.8), p=0.02). Dyslipidaemia, obesity, and vitamin D insufficiency were highly prevalent in the study group. Poorly controlled blood glucose was associated with vitamin D insufficiency. The high prevalence of dyslipidaemia, obesity and vitamin D deficiency are the possible precipitating factors for the increasing rates of cardiovascular events and COVID-19 severity among patients with diabetes in Malawi. [ABSTRACT FROM AUTHOR]