# Reporting and handling of missing data in published studies of co-morbid hypertension and diabetes among people living with HIV/AIDS: a systematic review

## TL;DR

This paper reviews how missing data is reported and handled in studies on hypertension and diabetes among people with HIV/AIDS, finding significant gaps in proper data management.

## Contribution

The study systematically evaluates the extent and methods of handling missing data in co-morbid hypertension and diabetes research among PLWH.

## Key findings

- Only 34.4% of included studies reported missing data, mostly in exposure variables like CD4 count.
- Complete case analysis was the most common method used to handle missing data.
- Only 9.43% of studies used multiple imputation, and few acknowledged potential biases from missing data.

## Abstract

As hypertension and diabetes emerge as co-morbidities among people living with HIV/AIDS (PLWH), the need for robust epidemiological research to inform policy and action is imperative. Proper reporting and handling of missing data are crucial in such studies to avoid loss of statistical power and precision and generate unbiased results. We aimed to assess the reporting and handling of missing data in published studies of co-morbid hypertension and diabetes among PLWH.

We searched in PubMed for cross-sectional studies of co-morbid hypertension and diabetes among PLWH published worldwide between January 1990 and June 2023. We extracted data on reporting of missing data (quantity, type, where it occurred, and any bias assessment) and how it was handled.

Of 2179 records identified, 154 studies were included among which 53 (34.4%) reported missing data, primarily within exposure variables such as CD4 count and viral load. Only 19 of these studies (37.7%) cited reasons for missingness, predominantly attributed to lack of documentation and non-response. Out of the 24 (45.5%) studies that detailed how they handled missing data, the majority (16 studies; 30.2%) used complete case analysis. Only 5/53 studies (9.43%) adopted multiple imputation methods. The potential biases introduced by missing data were acknowledged in only 12/53 (22.6%) studies.

The reporting and handling of missing data in hypertension and diabetes studies among PLWH are currently suboptimal. Enhanced understanding of why data is missing and choosing appropriate methods to address it is paramount to reduce potential biases. Adopting and adhering to comprehensive guidelines for managing missing data is a pressing need and will ensure that more accurate results are better represented in PLWH population.

The online version contains supplementary material available at 10.1186/s12874-025-02630-1.