Community based hematological reference intervals among apparently healthy adolescents aged 12-17 years in Mekelle city, Tigrai, northern Ethiopia: A cross sectional study

Association of healthy lifestyle score with control of hypertension among treated and untreated hypertensive patients: a large cross-sectional study

Background

Hypertension stands as the leading single contributor to the worldwide burden of mortality and disability. Limited evidence exists regarding the association between the combined healthy lifestyle score (HLS) and hypertension control in both treated and untreated hypertensive individuals. Therefore, we aimed to investigate the association between HLS and hypertension control among adults with treated and untreated hypertension.

Methods

This cross-sectional study, including 311,994 hypertension patients, was conducted in Guangzhou using data from the National Basic Public Health Services Projects in China. The HLS was defined based on five low-risk lifestyle factors: healthy dietary habits, active physical activity, normal body mass index, never smoking, and no alcohol consumption. Controlled blood pressure was defined as systolic blood pressure <140 mmHg and diastolic blood pressure <90 mmHg. A multivariable logistic regression model was used to assess the association between HLS and hypertension control after adjusting for various confounders.

Results

The HLS demonstrated an inverse association with hypertension control among hypertensive patients. In comparison to the low HLS group (scored 0-2), the adjusted odds ratios (95% confidence intervals) for hypertension were 0.76 (0.74, 0.78), 0.59 (0.57, 0.60), and 0.48 (0.46, 0.49) for the HLS groups scoring 3, 4, and 5, respectively (Ptrend < 0.001). Notably, an interaction was observed between HLS and antihypertensive medication in relation to hypertension control (Pinteraction < 0.001). When comparing the highest HLS (scored 5) with the lowest HLS (scored 0-2), adjusted odds ratios (95% confidence intervals) were 0.50 (0.48, 0.52, Ptrend < 0.001) among individuals who self-reported using antihypertensive medication and 0.41 (0.38, 0.44, Ptrend < 0.001) among those not using such medication. Hypertensive patients adhering to a healthy lifestyle without medication exhibited better blood pressure management than those using medication while following a healthy lifestyle.

Conclusion

HLS was associated with a reduced risk of uncontrolled blood pressure.

Association of adiposity indicators with cardiometabolic multimorbidity risk in hypertensive patients: a large cross-sectional study

Background

Cardiometabolic multimorbidity (CMM) has emerged as a prominent public health concern. Hypertensive patients are prone to develop comorbidities. Moreover, the accumulation of visceral adipose tissue is the main cause for the development of cardiometabolic diseases. The cardiometabolic index (CMI), lipid accumulation product (LAP), visceral adiposity index (VAI), and Chinese visceral adiposity index (CVAI) not only assess adipose tissue mass but also reflect adipose tissue dysfunction. So far, no study has been reported to evaluate the association of CMI, LAP, VAI, and CVAI with CMM risk in hypertensive patients. Therefore, this study aimed to assess the association between these adiposity indicators and the risk of CMM among Chinese hypertensive patients.

Methods

In this cross-sectional study, a total of 229,287 hypertensive patients aged 35 years and older were included from the National Basic Public Health Service Project. All participants underwent a face-to-face questionnaire survey, physical examination, and the collection of fasting venous blood samples. Multivariable logistic regression models were performed to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Receiver operating characteristic curve was utilized to evaluate the identification ability for CMM.

Results

After adjusting for confounders, each 1-standard deviation increase in CMI, LAP, VAI, and CVAI was associated with a 14%, 8%, 12%, and 54% increased risk of CMM, respectively. When comparing the highest quartile of these indicators with the lowest quartile, individuals in the highest quartile of CMM, LAP, VAI, and CVAI had a 1.39-fold (95% CI 1.30, 1.48), 1.28-fold (95% CI 1.19, 1.37), 1.37-fold (95% CI 1.29, 1.46), and 2.56-fold (95% CI 2.34, 2.79) increased risk of CMM after adjusting for potential confounders. Notably, a nonlinear association was observed for CMI, LAP, and VAI with the risk of CMM (all P nonlinearity < 0.001). CVAI exhibited the highest area under the receiver operating characteristic curve (AUC) among all the included adiposity indices in this analysis.

Conclusion

This study indicated the significant positive association of CMI, LAP, VAI, and CVAI with the risk of CMM in hypertensive patients. Among these indicators, CVAI demonstrated the most robust performance in predicting CMM risk and may serve as a valuable tool for identifying CMM risk in Chinese hypertensive patients.

Region-specific laboratory reference intervals are important: A systematic review of the data from Africa

Region-specific laboratory reference intervals (RIs) are important for clinical trials and these data are often sparse in priority areas for research, including Africa. We reviewed data on RIs from Africa to identify gaps in the literature with a systematic review of PubMed for RI studies from Africa published ≥2010. Search focus included clinical analytic chemistry, hematology, immunological parameters and RIs. Data from adults, adolescents, children, pregnant women, and the elderly were included. We excluded manuscripts reporting data from persons with conditions that might preclude clinical trial participation in studies enrolling healthy volunteers. Of 179 identified manuscripts, 80 were included in this review, covering 20 countries with the largest number of studies in Ethiopia (n = 23, 29%). Most studies considered healthy, nonpregnant adults (n = 55, 69%). Nine (11%) studies included pregnant women, 13 (16%) included adolescents and 22 (28%) included children. Recruitment, screening, enrollment procedures and definition of age strata varied across studies. The most common type of RIs reported were hematology (66, 83%); 14 studies (18%) included flow cytometry and/or T cell counts. Other common tests or panels included liver function assays (32, 40%), renal function assays (30, 38%), lipid chemistries (17, 21%) and serum electrolytes (17, 21%). The number of parameters characterized ranged from only one (three studies characterized either CD4+ counts, D-dimer, or hemoglobin), to as many as 40. Statistical methods for calculating RIs varied. 56 (70%) studies compared their results to international RI databases. Though most presented their data side-by-side with international data with little accompanying analysis, nearly all reported deviation from comparator RI data, sometimes with half or more of otherwise healthy participants having an "out of range" result. We found there is limited local RI data available in sub-Saharan Africa. Studies to fill this gap are warranted, including efforts to standardize statistical methods to derive RIs, methods to compare with other RIs, and improve representative participant selection.