Background: Peripartum cardiomyopathy (PPCM) is a life-threatening heart muscle disease of unknown aetiology that affects women during the peripartum period, particularly in sub-Saharan Africa. While many studies have observed normal blood pressure (BP) in PPCM patients, none have explored whether their BP is appropriate for their body size. This study investigated the correlation between body anthropometric parameters and BP in PPCM patients, comparing the findings with those of age-matched normal peripartum controls. Methods: A cohort of 105 women, each from PPCM and matched normal peripartum control groups, were recruited from three healthcare facilities in Sokoto. Blood pressure (BP) parameters were assessed in relation to their anthropometric measurements, and the findings were compared between the two groups. Results: The PPCM patients were significantly smaller in body weight (57.0 ±11.6 Kg vs 66.8 ±13.8 Kg, P <.0001), body mass index (BMI) (21.9 ±4.1 Kg/m2 vs 25.4 ±5.4 Kg/m2, P <.0001, body surface area (BSA) (1.3 ±0.7 m2 vs 1.7 ±0.2 m2, P <.0001), Lean body mass (LBM) (45.3 ±7.0 Kg vs 49.4 ±4.1 Kg, P <.0001) and Percentage body fat (BF) (23.5 ±10.9 % vs 31.2 ±6.9 %, P <.0001). Similarly, PPCM patients had significantly higher systolic BP (SBP), Pulse pressure (PP) and Mean arterial blood pressure (MABP) compared to the normal peripartum PPCM control. Further, linear regression analysis showed that there was higher slope of the relationship between anthropometric indices and SBP and PP in the PPCM cohort, compared to the normal peripartum control group. A similar trend of the slope was seen in the Pearson’s coefficient of the relationship of the anthropometries and BP parameters. Conclusions: This study found that women with peripartum cardiomyopathy (PPCM) exhibited disproportionately higher systolic blood pressure (SBP) and pulse pressure (PP) for each unit increase in anthropometric measurements compared to normal peripartum controls. Notably, PPCM patients had significantly lower anthropometric measures, potentially attributable to poverty and chronic undernutrition. Additionally, the effects of poor antenatal care, lack of immunization and recurrent infection should be considered. These findings suggest an abnormal relationship between anthropometry and blood pressure in PPCM patients, which may have detrimental effects on their cardiovascular health. This abnormal relationship may contribute to the development of heart failure (HF) in PPCM patients and potentially increase the risk in women susceptible to PPCM. Even-though our assumption, yet to be proven. To address this concerning trend in vulnerable populations, improvements in nutritional status, socioeconomic determinants health, adequate antenatal care (ANC), immunization, and infection prevention should be considered.

An unhealthy dietary habit leads to excess calorie consumption (overnutrition) or inadequate supply of one or more essential micronutrients (undernutrition).This nutritional imbalance is assessed by Anthropometric measurements, Biochemical estimations, Clinical examination and assessment of Dietary intakes. Anthropometry is an inexpensive, rapid and non-invasive method that provides details on different components of body structure and is highly sensitive to the broad spectrum of nutritional status. Hence, it has always been an important tool for screening and early diagnosis of malnutrition. Undernutrition in below 5 year children is life-threatening epidemic contributing to about 45% of under 5 child deaths. Children with Severe Acute Malnutrition (SAM) are nine times more likely to die, compared to their healthy counterparts. Therefore, early and accurate diagnosis of children with SAM is crucial for its management and prevention of morbidity and mortality from the same. SAM is defined as weight-for-height Z scores (WHZ) below -3SD of the median or a mid upper arm circumference (MUAC) of <115mm in children of 6-59 months age. The cut-offs for MUAC and WHZ are scientifically approximated to each other and both are used to diagnose children with SAM (Severe Wasting). However, the research findings from various countries revealed that the agreement between WHZ and MUAC is poor as both indices classify the children with SAM differently, with a small overlap, which varies greatly among countries. These discrepancies have an implication when using either one alone for measuring the prevalence of acute malnutrition. Therefore, it is pertinent to adopt both WHZ and MUAC indices to assess the burden of severe acute malnutrition (SAM) in the community.