Comparison of nutritional status and dietary intake among khat (Catha edulis) chewer and non-chewer women of reproductive age in Halaba Zone, South Ethiopia: a comparative cross-sectional study

Abstract

Objective

This study aimed to compare the nutritional status and dietary intake between khat chewer and non-chewer women of reproductive age in Halaba Zone, South Ethiopia.

Design

A comparative cross-sectional study was conducted.

Setting

The study was conducted in Halaba Zone, South Ethiopia.

Participants

A total of 792 (396 khat chewers and 396 non-chewers) women of reproductive age were selected by a simple random sampling technique from 20 June 2023 to 26 August 2023.

Outcome measures

Dietary intake was assessed by a single 24-hour recall method. The nutrient adequacy ratio and mean adequacy ratio were applied to estimate the adequacy of micronutrients. Standing height was measured using a wall-mounted stadiometer to the nearest 0.1 cm, and weight of the women was measured to the nearest 0.1 kg on a battery-powered digital scale (Seca Gmbh & Co. KG, Germany). A linear regression model was fitted to determine the relationship between nutritional status and khat chewing. Binary logistic regression analyses were used to estimate the odds of nutrient intake inadequacy among the two study groups. A p value of <0.05 was considered statistically significant at 95% CI.

Results

Women who chewed khat had a higher prevalence of underweight (36.6%) than those who did not (9.4%). The mean (SD) body mass index for khat chewer women was 48.66±5.39 kg, while that of non-chewer women was 55.29±6.75 kg. Women who chewed khat were significantly more likely to be underweight than those who had never chewed khat (β = −1.91, 95% CI −2.30 to –1.53; p<0.001). The analysis revealed that out of the nine nutrients assessed, the intake of seven nutrients was significantly lower in khat-chewer women compared with non-chewer women. Women who chewed khat were more likely to have inadequate carbohydrate (AOR=2.05 (95% CI 1.31 to 3.21), p<0.01), protein (AOR=2.18 (95% CI 1.51 to 3.14), p<0.001), thiamine (AOR=4.25 (95% CI 2.72 to 6.63), p<0.001), riboflavin (AOR=4.02 (95% CI 2.48 to 6.50), p<0.001), niacin (AOR=2.34 (95% CI 1.59 to 3.45), p<0.001), vitamin B₁₂ (AOR=2.79 (95% CI 1.79 to 4.36), p<0.001), calcium (AOR=2.22 (95% CI 1.55, 3.18), p<0.001) and zinc (AOR=3.57 (95% CI 1.92 to 6.61), p<0.001).

Conclusions

Women who chewed khat were significantly more likely to be underweight compared with those who had never chewed khat. Khat chewers were more likely than non-chewers to have inadequate carbohydrate, protein, thiamine, riboflavin, niacin, vitamin B₁₂, zinc and calcium intake. Public health interventions aimed at improving the nutritional status of women of reproductive age should develop strategies to address the spread of khat-chewing habits.

STRENGTHS AND LIMITATIONS OF THIS STUDY.

• An interactive, multiple-pass 24-hour dietary recall questionnaire was used to assess dietary intake, which improved accuracy and completeness of dietary data.

• Minimum dietary diversity for women of reproductive age, which is a validated and globally recognised tool, has been used to measure dietary diversity score among women of reproductive age.

• The study included women of reproductive age from both urban and rural areas, increasing the study’s generalisability.

• The study was conducted at a single point in time and does not depict the dynamics of changes in women’s nutritional status and nutrient consumption.

• Nutrient intakes were not adjusted to get the usual intake distribution since only single-day intakes were obtained by 24-hour recall.

Introduction

Khat (Catha edulis) is a recreational, chewed herbal drug that has been used as a psychostimulant for centuries in the Arabian Peninsula and East Africa.¹ Globally, more than 10 million people are habitual khat consumers.² In the past few decades, khat chewing by women was considered forbidden in Ethiopia, but its consumption among women has recently increased and become socially accepted.³ According to the 2016 Ethiopian Demographic and Health Survey (EDHS), 12% of women have ever chewed khat on a national scale.⁴

The regional distribution of khat usage during pregnancy in Ethiopia ranges from 9.9% to 35.8% in southern Ethiopia,^{5 6} 15.5% to 60.4% in the Harar area7,10 and 5.8% to 65.8% in the Oromia region.11,14 According to a recent systematic review and meta-analysis of studies conducted over the past 10 years, the pooled prevalence of khat usage during pregnancy in Ethiopia was 26%.¹⁵ Fresh khat leaves contain over 40 different chemicals.^{16 17} Cathinone, classified as a controlled substance in many countries,¹⁸ is the main psychoactive chemical in fresh khat leaves, with levels ranging between 78 and 343 mg per 100 g of leaves.¹⁹

The potential side effects of khat affect several organs in the body. Khat chewing is associated with some positive mental experiences, such as euphoria, elevated imagination and increased self-confidence in the early stages of use; however, these are eventually followed by adverse symptoms including nervousness, anxiety, depression and insomnia.^{1 20} Long-term khat use is often linked to cardiac, psychological, neurological and gastrointestinal disorders.²¹ Khat chewing during pregnancy has a number of adverse effects, including low birth weight22,25 and prelabour membrane rupture.¹⁰

Cathinone causes appetite suppression after khat intake, working centrally in the hypothalamus to delay stomach emptying.^{26 27} Additionally, khat chewing is commonly linked with a variety of gastrointestinal irritative diseases, including gastritis and constipation.^{19 26 28}

Studies from Addis Ababa²⁹ and Jimma town³⁰ have linked khat chewing to undernutrition. One study from Eastern Ethiopia shows that undernutrition is much more common among lactating women who chew khat than among those who do not,³¹ underscoring the possible effects of khat chewing on maternal health and nutritional status.

Despite an expanding body of studies on khat, studies on its effect on women’s nutritional status and food intake remain limited.³² Women in this age group, who are biologically capable of becoming pregnant and experience menstrual cycles,³³ are particularly susceptible to the effects of khat use during pregnancy.^{10 22 23 25 34 35} Studying the nutritional status and dietary intake of women of reproductive age is crucial, as their nutritional health directly impacts their own well-being as well as the health outcomes of their future pregnancies and children. Furthermore, psychoactive substances affect women differently than men due to various physiological, biochemical and behavioural differences.³⁶

Previous nutritional studies primarily focused on the nutritional status of khat chewers.^{30 31} However, these studies did not employ multivariable analysis to examine the independent impact of khat on nutritional status. There also appears to be a dearth of research that examines the associations between khat chewing habits and the nutrient intake of women of reproductive age. A more systematic approach is needed to develop nutritional interventions aimed at improving the health of women who chew khat, with a clearer understanding of how khat chewing affects their dietary intake. Therefore, the purpose of this study was to compare dietary diversity, nutrient intake and nutritional status between khat chewers and non-chewers of women of reproductive age in Halaba Zone, South Ethiopia.

Materials and methods

Study design, area and period

A community-based comparative cross-sectional study was conducted in the Halaba Zone. Halaba Zone is located in Southwest Ethiopia, 315 km from Ethiopia’s capital city, Addis Ababa. The altitude of this zone ranges from 1700 to 2200 metres above sea level, except for areas that slope down to the shore of Lake Shala. The Halaba Zone comprises 79 rural and 5 urban kebeles (the smallest administrative divisions in Ethiopia) and has a total population of 301 658, with 151 545 females and 244 582 (80.1%) residing in rural areas.³⁷ The zone has 74 health posts, 7 health centres and 1 primary-level hospital. According to the Halaba Zone Agriculture Administration, the zone is known for farming cash crops such as khat, pulses and pepper. The population is predominantly Muslim; therefore, data collection took place from June 20 to August 26, 2023, a period outside of fasting times.

Population

Study population

All current khat chewer and non-chewer women of reproductive age who lived at the selected kebeles during the data collection periods were taken as a study population.

Inclusion criteria

• Current khat chewer and non-chewer women of reproductive age (15–49 years) who lived for at least 6 months in Halaba Zone.

Exclusion criteria

• Women of reproductive age who are mentally or critically ill and unable to communicate.

• Women who were pregnant during the data collection period.

• Women who did not provide consent to participate.

Sample size determination and sampling technique

The sample size was determined by using the double population proportion formula via Epi Info V.7.2.5.0 with the following assumptions: the proportion underweight among khat chewer women (P₁=39.0%) and non-chewers (P₂=22.4%),³¹ 5% margin of error, 90% of power, 1:1 khat chewer to non-chewer ratio, a design effect of 2 and a 15% non-response rate. The final sample size was 792 (396 from khat chewers and 396 from non-chewers). To select research participants, a multistage stratified sampling procedure was used. Out of four districts in the zone, three were selected randomly. The selected districts were then divided into rural and urban kebeles. Then, 11 of 44 rural kebeles and 1 of 5 urban kebeles (25%) were chosen at random.

A census was conducted to obtain a list of khat chewer and non-khat chewer women households in each selected kebele, which was used as a sampling frame. At first, the research team worked with kebele leaders and community elders to get into the community and get support. Data collectors used family folders, health post records and community health information systems kept up by health extension workers. These systems often have basic demographic information like age. A sampling frame was prepared by registering all identified eligible khat chewer and non-chewer women of reproductive age in each selected kebele. The number of khat-chewer and non-chewer women chosen was then distributed proportionally to each kebele based on the size of their respective study population. A simple random sampling technique was used to get both khat chewer and non-chewer women from each kebele by using computer-generated random numbers. When more than one eligible woman was found in a selected household, the lottery method was used to select one eligible woman (figure 1).

Figure 1. Schematic presentation of sampling procedures followed to get study participants in Halaba Zone, Southern Ethiopia, 2023 (N=792). AC, Andegna Choroqo; AH, Andegana Hansha; AT, Alem Tena; GA, Galato; GE, Gedeba; HC, Huletegna Choroqo; HH, Huletegna Hansha; KF, Kufe; LB, Lenda Beri; LL, Layegnawo Lenda; TL, Tachignaw Lenda; WW, Wanjana Woldia.

Standard and operational definitions

• Khat chewers: women who reported khat chewing at least weekly in the previous 3 months and non-chewers refer to a woman who did not consume khat in her lifetime and/or a woman who has consumed khat in her lifetime but has not consumed it weekly within 3 months prior to the data collection period.³⁸ Khat primarily contains the active compound cathinone. Cathinone can indeed cause rapid weight loss, often within a few weeks (4 weeks) after chewing khat.³⁹ This is primarily due to their strong appetite-suppressing effects and the increase in metabolic rate they induce. According to the Alcohol, Smoking and Substance Involvement Screening Test manual, the frequency of substance use in the past 3 months gives an indication of the substances which are most relevant to current health status.³⁸

• Woman with chronic disease: refers to a woman who has been diagnosed with a long-term medical condition (hypertension, diabetes, heart disease, renal failure, asthma, chronic obstructive pulmonary disease, epilepsy or other medical conditions) that persist over an extended period.

• Underweight: women with body mass index (BMI) less than 18.5 kg/m².⁴⁰

• Adequate dietary diversity: women who consumed less than five food categories were considered to have an inadequately diverse diet, whereas those who consumed five or more food groups were considered to have an adequate dietary diversity.⁴¹

• Inadequate intake of carbohydrates: refers to a situation where the proportion of total daily calories derived from carbohydrates is less than 45% of the total caloric intake.⁴²

• Inadequate intake of protein: refers to a situation where the proportion of total daily calories derived from protein is less than 10% of the total caloric intake.⁴²

• Inadequate intake of particular micronutrient: when a micronutrient’s daily consumption value was less than its estimated average requirements (EAR).⁴³

• Inadequate intake of particular micronutrient: when a nutrient adequacy ratio (NAR) micronutrient’s daily consumption value is less than 1.⁴⁴

• Overall micronutrient intake inadequacy: when an individual’s intake mean adequacy ratio (MAR) for micronutrients was less than 1.⁴⁴

Data collection tool and measurements

Data were collected using a structured interviewer-administered questionnaire by seven trained community health workers through house-to-house visits. The questionnaire was initially developed in English and then translated into Amharic, the local language, by a fluent bilingual individual. Information on socio-demographics, history of chronic illness, dietary practices and anthropometric data was collected (online supplemental file 1).

Socio-demographic and economic data were gathered using a structured questionnaire adapted from the EDHS 2016 survey.⁴⁵ Variables included to construct the wealth index were house and land ownership, housing quality (eg, construction materials), household assets and access to services (such as electricity, water and sanitation services).⁴⁵

Dietary diversity determination

Dietary intake was assessed by a single 24-hour recall method. To gather the dietary intake information, participants were asked to recall the foods they had consumed in the previous 24-hour foods consumed including food eaten inside and outside the home. A dietary diversity score was computed in accordance with the Food and Agriculture Organization’s guideline for minimum dietary diversity for women of reproductive age (MDD-W).⁴¹ MDD-W is a dichotomous indicator of whether or not women aged 15–49 years have eaten at least 5 out of 10 identified food groups the previous day or night.⁴⁶ It is a food group diversity indicator that measures one important aspect of diet quality. Micronutrient adequacy is summarised across 11 micronutrients, including vitamin A, vitamin B₁ (thiamin), vitamin B₂ (riboflavin), vitamin B₃ (niacin), vitamin B₆ (pyridoxine), folate, vitamin B₁₂, vitamin C, iron, calcium and zinc.⁴⁶

To calculate MDD-W, reported food items were categorised into 10 food groups: (1) white roots/grains and tubers; (2) pulses (beans, lentils and peas); (3) nuts and seeds; (4) dairy; (5) meat, fish and poultry; (6) eggs; (7) dark green leafy vegetables; (8) other vitamin-A rich vegetables and fruits; (9) other vegetables; and (10) other fruits. Other vitamin A-rich vegetables and fruits group consists of both vitamin A-rich fruits and a small but diverse group of vitamin A-rich vegetables other than leafy greens. To determine whether food items from a certain food group were consumed or not, consumption of each food category was converted into binary variables (1=yes, 0=no). After calculating the MDD-W, women were classified as having an adequate or inadequate dietary variety.⁴¹

Measurement of nutrient intake

An interactive, multiple-pass 24-hour dietary recall questionnaire was used to assess all foods, drinks and snacks consumed from midnight of the previous day to midnight of the following day. The dietary interviews for this survey were arranged in the ‘Four Passes Method’, as suggested by Gibson and Ferguson,⁴⁷ to improve participant memory. In the first pass, women were asked to report a quick list of all foods, snacks and drinks consumed from midnight of the previous day to midnight of the following day. In the second pass, complete descriptions of meals and beverages consumed, including cooking techniques and brand (trade) names, were obtained. Furthermore, respondents were asked if they remembered any meals or drinks they had consumed but were not included in the initial pass. In the third pass, the portion sizes of each food and drink were estimated using household measurement aids such as cups, spoons, ladles and bowls. To minimise recall bias in 24-hour dietary recalls, a multiple-pass strategy was adopted, which guided participants through stages of recalling foods and visual aids such as portion size graphics and food models helping with memory and quantity estimate.

The portion sizes were weighed using a digital household dietary scale (Omron Electronic Kitchen Scale, Omron, Tokyo, Japan) to convert household measures into grams. Respondents were asked to list all food types and ingredients for mixed dish foods. The energy and nutrient content (both macro and micro) of each food item was determined using the Ethiopian Food Composition Table Part IV.⁴⁸ The Tanzania and Kenya Food Composition Tables were also used to extract the nutrient values for food items not included in the Ethiopian Food Composition Table.^{49 50} The nutrient content of each consumed food item per standard serving size (100 g) was obtained from the food composition table. To calculate the nutrient intake for the actual portion size consumed, we used the following formula (equation 1):

$${\displaystyle \begin{array}{l}Nutrient\\ intake\end{array}=\begin{array}{l}\frac{\mathrm{N}\mathrm{u}\mathrm{t}\mathrm{r}\mathrm{i}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{p}\mathrm{e}\mathrm{r}\mathrm{S}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{d}\mathrm{a}\mathrm{r}\mathrm{d}\mathrm{S}\mathrm{e}\mathrm{r}\mathrm{v}\mathrm{i}\mathrm{n}\mathrm{g}}{StandardServingSize}\end{array}\times \begin{array}{l}Actual\\ PortionSize\end{array}}$$ (1)

If a woman consumed multiple foods, her nutrient intake was calculated for each food item and then summed to determine her total intake of that nutrient.

Assessment of nutrient adequacy

Micronutrient adequacy was assessed using the NAR and the MAR. First, the NAR for the nutrients was computed before MAR. The NAR of a given nutrient was estimated as a ratio of the actual intake of the nutrient per day to age-specific and sex-specific EAR. The EAR is the daily nutrient intake level estimated to meet the requirements of 50% of the healthy individuals in a particular life stage and gender group.⁵¹ The age-specific and sex-specific EARs were adapted from the recommendation developed by the Institute of Medicine of the National Academies. After computing the NARs for each individual micronutrient, the ratios that were higher than 1 were truncated to 1. As a result, nutrients with a high NAR value could not compensate for micronutrients with a low NAR value. NAR was truncated to zero when it was less than 1. The MAR was calculated as the sum of all NARs divided by the number of nutrients by truncating the NAR of each nutrient as indicated in the equation below (equation 2 and 3).⁴⁴

$${\displaystyle \mathrm{N}\mathrm{A}\mathrm{R}=\frac{\mathrm{D}\mathrm{a}\mathrm{i}\mathrm{l}\mathrm{y}\mathrm{d}\mathrm{i}\mathrm{e}\mathrm{t}\mathrm{a}\mathrm{r}\mathrm{y}\mathrm{n}\mathrm{u}\mathrm{t}\mathrm{r}\mathrm{i}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{i}\mathrm{n}\mathrm{t}\mathrm{a}\mathrm{k}\mathrm{e}}{\mathrm{E}\mathrm{s}\mathrm{t}\mathrm{i}\mathrm{m}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{d}\mathrm{a}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}\mathrm{e}\mathrm{r}\mathrm{e}\mathrm{q}\mathrm{u}\mathrm{i}\mathrm{r}\mathrm{e}\mathrm{m}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{o}\mathrm{f}\mathrm{t}\mathrm{h}\mathrm{a}\mathrm{t}\mathrm{n}\mathrm{u}\mathrm{t}\mathrm{r}\mathrm{i}\mathrm{e}\mathrm{n}\mathrm{t}}}$$ (2)

$${\displaystyle \mathrm{M}\mathrm{A}\mathrm{R}=\frac{\sum \mathrm{N}\mathrm{A}\mathrm{R}\left(truncatedat1\right)}{\mathrm{N}\mathrm{u}\mathrm{m}\mathrm{b}\mathrm{e}\mathrm{r}\mathrm{o}\mathrm{f}\mathrm{n}\mathrm{u}\mathrm{t}\mathrm{r}\mathrm{i}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{s}}}$$ (3)

The percentage distribution of the macronutrients with respect to total energy intake was assessed according to the acceptable macronutrient distribution ranges (AMDR). For adults, the AMDR for carbohydrate, protein and fat is 45–65%, 10–35% and 20–35% of total calories, respectively. For women aged 15–18 years, the AMDR for protein is 10–30% of total calories, while that for fat is 25–35% of total calories.⁴²

Estimated energy requirement (EER) was calculated to estimate the daily calorie intake necessary to maintain energy balance in a healthy individual, based on factors such as age, sex, weight, height and physical activity level. For women aged 19 years and older, the following formula was used to determine EER (equation 4).⁴³

$${\displaystyle \mathrm{E}\mathrm{E}\mathrm{R}=\begin{array}{l}135.3-(30.8\times \mathrm{a}\mathrm{g}\mathrm{e}[\mathrm{y}])\\ +\mathrm{P}\mathrm{A}\times [(10\times \mathrm{w}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}[\mathrm{k}\mathrm{g}])+(934\times \mathrm{h}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}[\mathrm{m}])]+25\end{array}}$$ (4)

EER was also computed using the following formula for women aged 19 years and older (equation 5).⁴³

$${\displaystyle \mathrm{E}\mathrm{E}\mathrm{R}=\begin{array}{l}354-(6.91\times \mathrm{a}\mathrm{g}\mathrm{e}[\mathrm{y}])\\ +\mathrm{P}\mathrm{A}\times [(9.36\times \mathrm{w}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}[\mathrm{k}\mathrm{g}])+(726\times \mathrm{h}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}[\mathrm{m}])]\end{array}}$$ (5)

Where PA (physical activity coefficient) = 1 for sedentary, 1.16 for low active, 1.31 for active and 1.56 for very active women under 19 years of age. For women aged 19 years or older, PA=1 for sedentary, 1.12 for low active, 1.27 for active and 1.45 for very active.⁴³ The proportions of women with intakes below the lower bounds of the AMDR for fat, protein and carbohydrate were also examined. The percentage of calories from each macronutrient was compared with the AMDR percentages for the studied macronutrients. Grams of protein and carbohydrate were converted to calories (4 kcal/g), and then divided by EER to generate percentages of protein and carbohydrate. Grams of total fats were converted to calories (9 kcal/g) and then divided by EER to generate percentages of total fats.⁵²

Anthropometric measurements

Standing height was measured using a wall-mounted stadiometer, and weight was measured using a battery-powered digital scale (Seca GmbH & Co.KG, Germany). The stadiometer was mounted on a flat and vertical surface. For height measurement, the women stood straight, barefoot, with heels together, and head positioned in the Frankfort plane, with the measurement recorded to the nearest 0.1 cm. The digital scale was placed on a flat and hard surface. For weight measurement, the women stood centred on the scale, barefoot and in light clothing, with the weight recorded to the nearest 0.1 kg.⁵³

Nutritional status was evaluated using the BMI. The BMI of the study subjects was calculated by dividing the weight in kilogram by height in metre squared (kg/m²). BMI was classified according to the WHO classification: underweight (<18.5 kg/m²), normal weight (18.5–24.99 kg/m²), overweight (25.00–29.99 kg/m²) and obese (≥30.0 kg/m²).⁴⁰

Data quality management and control

We conducted a pretest on 5% of the sample prior to data collection in non-selected kebeles. In addition, a 7-day training session was provided for supervisors and data collectors on data gathering producers, tools and research aims. Furthermore, supervisors frequently monitored the data collectors during the data collection operations. Before measuring, the weight scale was calibrated with a 1 kg standard weight, and the height measurement was verified using other metre tapes. In addition, before the analysis, the authors and an experienced data clerk entered and cleaned the data.

Data synthesis and analysis

Data were double entered using EpiData V.3.1 software and for further analysis exported to Stata (V.14.0) software. Continuous data was examined for normality using the Kolmogorov-Smirnov test. The mean and SD were calculated for parametric continuous variables. All categorical variables were described using the frequencies and percentages. Principal component analysis (PCA) was used to construct the household wealth index. The Kaiser-Meyer-Olkin (KMO) and Bartlett’s test of sphericity were used to evaluate the data’s appropriateness for PCA. The KMO measure was 0.78, indicating adequate sampling adequacy. Bartlett’s test of sphericity was significant (p<0.001), suggesting that the correlation matrix was not an identity matrix. These results confirmed that the data were suitable for PCA. The household characteristics and facilities were dichotomised as ‘not improved’ and ‘improved’. The wealth index was weighted for urban and rural areas and then combined to produce a single wealth index. The first component derived from the PCA was then used to classify wealth status into three groups (poor, middle and rich).

The weight and BMI difference between the two groups was compared using independent samples t-tests. A χ² test was conducted to compare categorical variables. Bi-variable binary logistic regression analysis was employed to compare macro and micro nutrient intake inadequacy between khat chewers and non-chewers, while multivariable binary logistic regression analysis was employed to compare macronutrient and micronutrient intake between khat chewers and non-khat chewers by controlling potential confounders. The Hosmer-Lemeshow test was used to assess the goodness-of-fit of the multivariable binary logistic regression. Multivariable linear regression analysis was employed to compare nutritional status between khat chewers and non-khat chewers by controlling confounders. Variables with a p value of <0.25 in the bi-variable regression analysis were entered into a multivariable regression. The R-square was used to report the model fitness of the multivariable linear regression. Differences were considered significant when the p value was <0.05. Study findings were presented narratively and supported by tables and figures.

Results

Socio-demographic and other characteristics of respondents

A total of 792 women of reproductive age were interviewed, with a response rate of 100%. This perfect response rate was ensured through multiple visits to households. The median (IQR) age of khat chewers and non-chewers was 28 (25–30) and 32 (27–38) years, respectively. The majority of khat chewers (65.9%) were between the ages of 25 and 34 years, whereas non-chewers were 35 or older (44.7%). The majority of women who chewed khat (91.4%) were illiterate, but 52.3% of women who never chewed khat were also illiterate. More than three-quarters of women in both groups were married at some point in their lives. Over 80% of the women had families with more than four members. The percentage of women with at least one chronic disease was 2.8% in khat chewers and 1.5% in non-chewers. There were significant differences between khat chewers and non-chewers concerning their socio-demographic characteristics, including age (p<0.001), religion (p<0.001), marital status (p<0.01), educational level (p<0.01) and residence (p<0.001) (table 1).

Table 1. Socio-demographic and other characteristics of khat chewer and non-chewer women in Halaba Zone, South Ethiopia, 2023 (N=792).

Variables	Total N (%)	Khat chewer n (%)	Non-chewer n (%)	X2 P value
Respondent age (year)				92.0 <0.001
15–24	127 (16.0)	81 (20.5)	46 (11.6)
25–34	434 (54.8)	261 (65.9)	173 (43.7)
35 and above	231 (29.2)	54 (13.6)	177 (44.7)
Religion				42.4 <0.001*
Muslim	692 (87.4)	390 (98.5)	302 (76.3)
Orthodox	89 (11.2)	6 (1.5)	83 (20.9)
Protestant	11 (1.4)	–	11 (2.8)
Marital status				10.6 <0.01
Single	96 (12.1)	33 (8.3)	63 (15.9)
Ever married	696 (87.9)	363 (91.7)	333 (84.1)
Level of education				159.1 <0.001*
Cannot read and write	569 (71.8)	362 (91.4)	207 (52.3)
Primary school	97 (12.3)	26 (6.6)	71 (17.9)
Secondary school	80 (10.1)	5 (1.3)	75 (18.9)
College and above	46 (5.8)	3 (0.7)	43 (10.9)
Household wealth status				0.59 0.742
Poor	245 (30.9)	119 (30.1)	126 (31.8)
Middle	271 (34.2)	134 (33.8)	137 (34.6)
Rich	276 (34.9)	143 (36.1)	133 (33.6)
Family size				14.9 <0.001
<4	71 (9.0)	51 (12.9)	20 (5.0)
≥4	721 (91.0)	345 (87.1)	376 (95.0)
Chronic disease				1.5 0.220
Yes	17 (2.1)	11 (2.8)	6 (1.5)
No	775 (97.9)	385 (97.2)	390 (98.5)
Residence
Rural	539 (68.1)	350 (88.4)	189 (47.7)	150.5 <0.001
Urban	253 (31.9)	46 (11.6)	207 (52.3)

p-values in bold are less than 0.05

^*Fisher’s exact test.

Anthropometric indices

The mean (SD) weight and BMI were 48.66± 5.39 kg, and 20.42± 2.36 kg/m², respectively, for khat chewer women and 55.29± 6.75 kg and 22.37± 2.27 kg/m², respectively, for non-chewer women (figure 2).

Figure 2. Box and whisker plot showing the median and median BMI and weight among khat chewer and non-chewer women. BMI, body mass index.

The prevalence of underweight was higher among khat chewer women (36.6%) than non-chewer (9.4%). Only 58.8% of khat chewers had normal body weight, compared with 83.8% of non-chewers. Only 4.6% khat chewers and 6.8% non-chewers were overweight or obese. The χ² test demonstrated a statistically significant difference in undernutrition and normal weight between khat chewers and non-chewers (p<0.001). There was no significant difference in the prevalence of overweight or obesity between women who chewed khat and those who did not (p>0.05) (figure 3).

Figure 3. Comparison of the degree of malnutrition between the study groups according to khat chewing status using a χ² test. BMI, body mass index.

The mean values of weight and BMI were significantly lower in khat chewer women than non-chewer women (p < 0.05). In univariate linear regression analyses, khat chewing was significantly associated with the weight and BMI of the study participants (p<0.05). A multivariable linear regression model was conducted to investigate the independent effect of khat on the anthropometric indices. Women who chewed khat were significantly more likely to have lower body weight compared with those who did not (β = −6.14, 95% CI −7.15 to –5.13; p<0.001 and has an adjusted R²=0.46). Similarly, khat chewers had significantly lower BMI compared with non-chewers (β = −1.91, 95% CI −2.30 to –1.53; p<0.001; adjusted R²=0.52). The adjusted R² of this model was 52.0%, indicating that independent variables can explain 52.0% of the variation in BMI, while other factors account for the remaining 48% of the variability (table 2).

Table 2. Comparison of anthropometric indices between khat chewer and non-chewer women using independent samples t-test, bi-variable and multivariable linear regression models.

Anthropometric indices	Khat chewer	Non-chewer	Unadjusted khat effect beta (β) (95%CI)‡	t	Adjusted khat effect beta (β) (95%CI)§
	Mean (±SD)†	Mean (±SD)†
Weight (kg)	48.66±5.39	55.29±6.75	−6.63 (−7.49 to −5.78)*	−11.93	−6.14 (−7.15 to −5.13)*
BMI (kg/m2)	20.42±2.36	22.37±2.27	−1.95 (−2.27 to −1.63)*	−9.70	−1.91 (−2.30 to −1.53)*

β was calculated with non-chewer as reference.

Adjusted R-square for weight model=0.46 (46.0%), p value≤0.001.

Adjusted R-square for BMI model=0.52 (52.0%), p value≤0.001.

^*P value less than 0.05.

^†Independent samples t-test.

^‡Examined by bi-variable linear regression.

^§Khat effect was examined by using multivariable linear regression (adjusted for age, religion, marital status, level of education, residence, household wealth status, family size).

BMI, body mass index.

Food groups and MDD-W

The findings showed that grains, roots and tubers groups were the most commonly consumed food groups among khat chewer (99.7%) and non-chewer women (100%), with no significant difference (p=0.317). Similarly, there were no significant differences in the consumption of other vegetables and other fruits between khat chewers and non-chewers (p=0.317 and p=0.06, respectively). However, the results identified significant differences in the consumption of pulses (khat chewer (65.4%), non-chewer (75.2%), p<0.002), milk and milk products (khat chewer (12.6%), non-chewer (25.0%), p<0.001), meat (khat chewer (2.8%), non-chewer (7.3%), p<0.01), eggs (khat chewer (4.8%), non-chewer (11.1%), p<0.01) and vitamin A-rich food items (khat chewer (18.2%), non-chewer (29.3%), p<0.001).

The mean (SD) dietary diversity score was 4.4 (±1.0) for khat chewers and 4.0 (±1.1) for non-chewers. Overall, 36.6% of women consumed ≥5 food groups, while 63.4% of women did not meet the minimum food diversity requirement. Based on the MDD-W score, 33.3% of khat chewers and 45.9% of non-chewers achieved their minimum food diversity. Significant differences were found in MDD-W scores between khat chewer and non-chewer women (χ²= 13.2, p<0.001) (figure 4).

Figure 4. Comparison of dietary diversity between khat chewer and non-chewer women in Halaba Zone, South Ethiopia (N=792). *p<0.05 significant by χ² test. (Foods rich in vitamin A: includes both vitamin A-rich fruits and vegetables other than leafy greens). MDD-W, minimum dietary diversity for women.

Macronutrients and micronutrients intake based on the 24-hr intake

The median percentage of energy requirement from carbohydrate for khat chewers and non-chewers was 54.5% and 64.8%, respectively. The median contribution of protein to the total energy intake was comparable between khat chewers and non-chewers (7.90% vs 9.80%). For khat chewers, the median values were recorded as vitamin A (0.06), thiamin (1.12), riboflavin (1.79), niacin (0.64), vitamin C (3.10), dietary folate (0.89), zinc (1.82) and calcium (0.80). In contrast, non-chewers exhibited higher median values: vitamin A (0.25), thiamin (2.04), riboflavin (2.14), niacin (0.9), vitamin C (3.36), dietary folate (1.06), zinc (3.73) and calcium (1.04). The median MAR among khat chewers was 0.50, while non-chewers had a higher median of 0.70 (table 3 and figure 5).

Table 3. Distribution of daily macronutrients, and NAR of micronutrients by khat chewing status among WRA in Halaba Zone, South Ethiopia, 2023 (N=792).

Nutrients	DRI	Total NAR or % of energy Median (IQR)	Khat chewer NAR or % of energy Median (IQR)	Non-chewer NAR or % of energy Median (IQR)
	AMDR/EAR
Carbohydrates (% of energy)*	45–65	61.00 (46.9–78.0)	54.50 (43.5–72.7)	64.8 (51.5–81.9)
Fat (% of energy)*	20″/25′–35	32.50 (26.5–43.7)	28.50 (22.1–35.4)	38.5 (29.7–51.2)
Protein (% of energy)*	10–30′/35″	8.80 (6.6–11.5)	7.90 (6.0–10.4)	9.80 (7.4–12.3)
Vitamin A (µg RAE/d)†	485ꞌ/500ꞌꞌ	0.10 (0.03–0.61)	0.06 (0.02–0.46)	0.25 (0.05–0.74)
Thiamin (mg/d)†	0.9	1.50 (0.91–2.26)	1.12 (0.64–1.73)	2.04 (1.26–2.68)
Riboflavin (mg/d)†	0.9	2.00 (1.12–4.20)	1.79 (0.83–4.00)	2.14 (1.35–4.48)
Niacin (mg/d)†	11	0.80 (0.51–1.08)	0.64 (0.40–0.94)	0.90 (0.64–1.28)
Vitamin B12 (µg/d)†	2.0	0	0	0 (0–0.18)
Vitamin C (mg/d)†	56ꞌ/60ꞌꞌ	3.30 (1.79–7.10)	3.10 (1.54–6.85)	3.36 (2.02–7.39)
Dietary folate (µg/d)†	330ꞌ/320ꞌꞌ	1.00 (0.67–2.17)	0.89 (0.57–2.84)	1.06 (0.77–1.88)
Iron (mg/d)†	7.9ꞌ/8.1ꞌꞌ	0	0	0 (0–0.13)
Zinc (mg/d)†	7.3ꞌ/6.8ꞌꞌ	2.50 (1.48–4.23)	1.82 (1.21–2.88)	3.73 (2.28–5,12)
Calcium (mg/d)†	1100ꞌ/800ꞌꞌ	0.90 (0.65–1.25)	0.80 (0.50–1.13)	1.04 (0.77–1.35)
MAR	–	0.60 (0.40–0.70)	0.50 (0.40–0.70)	0.70 (0.50–0.80)

EAR for 15–18 years; ꞌꞌEAR for 19–49 years.

DRI in bold are AMDRs and those in italic are EARs.

^*p-value less than 0.05

^†p-value less than 0.01

AMDR, acceptable macronutrient distribution range; DRI, dietary reference intake; EAR, estimated average requirement; µg/d, microgram per day; MAR, mean adequacy ratio; mg/d, milligram per day; NAR, nutrient adequacy ratio; RAE/d, retinol activity equivalent/day; WRA, women of reproductive Age.

Figure 5. Comparison of NAR and MAR of micronutrients between khat chewer and non-chewer women in Halaba Zone, South Ethiopia (N=792). *p<0.05. MAR, mean adequacy ratio; NAR, nutrient adequacy ratio.

Comparison of nutritional inadequacy between the two groups

In table 4, the data are presented as the proportion of women who reported intake below AMDR for macronutrients and NAR<1 for micronutrients among khat chewer and non-chewer women. Approximately 28% of khat chewers had carbohydrate intakes below the AMDR, compared with 15% of non-chewers. More than two-thirds (70.9%) of khat chewers had protein intakes below the AMDR. The percentage of women with inadequate intake of thiamine (41.7% vs 12.9 %), riboflavin (32.6% vs 12.9 %), niacin (78.5% vs 59.8%), vitamin B₁₂ (88.1% vs 72.7 %) and folate (55.3% vs 47.5%) was significantly higher among khat chewers compared with non-chewers. No significant difference was observed in the proportion of women with inadequate vitamin A and vitamin C intakes between khat chewers and non-chewers (p>0.05). The percentage of women with inadequate zinc (19.7% vs 5.0%) and calcium (68.7% vs 45.9%) intake was also significantly higher among khat chewers than non-chewers.

Table 4. Comparison of nutrient inadequacy among khat chewer and non-chewer women in Halaba Zone, South Ethiopia, 2023 (N=796): univariable and multivariable binary logistic regression.

Nutrient (DRI§) and khat chewing	Inadequacy n (%)‡	COR (95% CI)	AOR (95% CI)
Carbohydrate (<45% of total daily calories)
Khat chewer	110 (27.8)	2.11 (1.49 to 2.99)†	2.05 (1.31 to 3.21)*
Non-chewer (ref.)	61 (15.4)	1	1
Protein (<10% of total daily calories)
Khat chewer	281 (70.9)	2.25 (1.68 to 3.02)†	2.18 (1.51 to 3.14)†
Non-chewer (ref.)	206(52.0)	1	1
Vitamin A (NAR<1)
Khat chewer	335 (84.6)	1.37 (0.95 to 1.98)	1.33 (0.84 to 2.10)
Non-chewer (ref.)	317 (80.0)	1	1
Vitamin B1 (NAR<1)
Khat chewer	165 (41.7)	4.83 (3.39 to 6.89)†	4.25 (2.72 to 6.63)†
Non-chewer (ref.)	51 (12.9)	1	1
Riboflavin (NAR<1)
Khat chewer	129 (32.6)	3.27 (2.28 to 4.69)†	4.02 (2.48 to 6.50)†
Non-chewer (ref.)	51 (12.9)	1	1
Niacin (NAR<1)
Khat chewer	311 (78.5)	2.45 (1.79 to 3.36)†	2.34 (1.59 to 3.45)†
Non-chewer (ref.)	237 (59.8)	1	1
Folate (NAR<1)
Khat chewer	219 (55.3)	1.37 (1.03 to 1.81)*	1.46 (1.03 to 2.08)*
Non-chewer (ref.)	188 (47.5)	1	1
Vitamin B12 (NAR<1)
Khat chewer	349 (88.1)	2.78 (1.91 to 4.06)†	2.79 (1.79 to 4.36)†
Non-chewer (ref.)	288 (72.7)	1	1
Vitamin C (NAR<1)
Khat chewer	51 (12.9)	1.74 (1.09 to 2.78)*	1.53 (0.86 to 2.74)
Non-chewer (ref.)	31 (7.8)	1	1
Calcium (NAR<1)
Khat chewer	272 (68.7)	2.58 (1.93 to 3.45)†	2.22 (1.55 to 3.18)†
Non-chewer (ref.)	182 (46.0)	1	1
Zinc (NAR<1)
Khat chewer	78 (19.7)	4.61 (2.76 to 7.71)†	3.57 (1.92 to 6.61)†
Non-chewer (ref.)	20 (5.0)	1	1

Outcome variable is inadequacy of nutrients; ꞌEAR for 15–18 years; ꞌꞌEAR for 19–49 years; ref: reference category (non-chewers).

Bold adjusted ratio is p-value less than 0.05.

^*p<0.01

^†p<0.001

^‡The per cent of individuals who had inadequate intake (NAR<1).

^§Dietary recommended intake

AOR, adjusted OR (adjusted for age, marital status, education, family size, wealth status, residence and chronic disease); COR, crude OR (without adjustment for confounding factors); DRI, dietary reference intake; EAR, estimated average requirement; NAR, nutrient adequacy ratio.

Table 4 also reports the results from the bi-variable and multivariable analysis examining the association of khat chewing with nutritional inadequacy. After adjusting for other potential factors affecting nutrient intake, we found an adjusted association between khat chewing and nutritional inadequacy. The multivariable analysis revealed that, out of the nine nutrients assessed, the intake of seven nutrients was significantly lower in khat-chewer women compared with non-chewer women. Khat chewers were 2.05 times more likely to have carbohydrate intake below the AMDR (adjusted OR (AOR)=2.05; 95% CI (1.31 to 3.21)) and 2.18 times more likely to have protein intake below the AMDR (AOR=2.18; 95% CI (1.51 to 3.14)) compared with non-chewers.

Women who chewed khat had significantly higher inadequacy of vitamin B₁ (AOR=4.25; 95% CI (2.72 to 6.63)), riboflavin (AOR=4.02; 95% CI (2.48 to 6.50)), niacin (AOR=2.34; 95% CI (1.59 to 3.45)), folate (AOR=1.46; 95% CI (1.03 to 2.08)) and vitamin B₁₂ (AOR=2.79; 95% CI (1.79 to 4.36)) compared with non-chewers. However, there was no significant association between khat chewing status and inadequacy of vitamin A and vitamin C intake (p>0.05). Khat chewers were 2.22 times more likely to have inadequate calcium intake (AOR=2.22; 95% CI (1.55 to 3.18)) and 3.57 times more likely to have inadequate zinc intake (AOR=3.57; 95% CI (1.92 to 6.61)) than non-chewers. The Hosmer and Lemeshow goodness-of-fit test yielded a p value greater than 0.05, indicating a good fit of the model to the observed data.

Discussion

The present study aimed to compare nutrient intake and nutritional status between khat chewer and non-chewer women of reproductive age in Halaba Zone, South Ethiopia. To the best of our knowledge, this is the first study to examine the links between khat chewing and nutrient intake in Ethiopia.

The mean BMI of khat chewers in this study is consistent with that reported in a comparative cross-sectional study conducted in Eastern Ethiopia, which found a mean BMI of 20.30±3.10 kg/m².³¹ While the mean BMIs for both khat-chewer and non-chewer women fall within the ‘normal weight’ category, a significant proportion (36.6%) of khat-chewing women had a BMI below 18.5 kg/m². This finding aligns with the Eastern Ethiopia study, where the prevalence of underweight among khat-chewer women was 39.8%.³¹ Women with low BMI have serious health risks such as a higher risk of infection.^{54 55} Anaemia⁵⁶ and osteoporosis can result from chronic undernutrition,⁵⁷ which also impairs the immune system and increases the risk of maternal problems including preterm delivery and low birth weight.⁵⁸

Furthermore, a statistically significant difference was found when comparing the mean BMI between khat chewer and non-chewer groups. This finding is consistent with previous research from Harar, Eastern Ethiopia, which documented significant differences in mean BMI between khat chewers and non-chewers.³¹ Similarly, a study conducted in Jimma town reported that khat chewers had a lower BMI compared with their non-chewer counterparts.³⁰ Additionally, research among male adults in Addis Ababa identified khat chewing as a significant predictor of undernutrition.²⁹ Our results are also consistent with a systematic review and meta-analysis conducted in Ethiopia.³²

The appetite-suppressing properties of khat might account for the observed higher percentage of undernutrition among khat chewers compared with non-chewers. Evidence from animal and human studies suggests that khat may have appetite-suppressant effects.^{59 60} However, research on the impact of khat on human appetite remains sparse. Future investigations should focus on the physiological effects of khat, particularly its potential influence on taste perception and dietary choices.

In contrast, research conducted in Butajira found no significant relationship between BMI and khat chewing status.⁶¹ The disparity may be attributed to differences in the study areas and population. The current study was carried out in the Halaba Zone, an area with a high rate of khat production, and focused specifically on women of reproductive age. In contrast, the Butajira study examined a general adult population. Additionally, women are generally more susceptible to the adverse effects of substance use and dependence due to hormonal and physiological factors.⁶²

A study conducted in Gondar town found that carbohydrate, protein and fat constituted 55.3%, 13.7% and 30.9% of total energy intake, respectively, which is comparable to our results of 61.0%, 8.8% and 32.5%. Our finding also indicated that only 30% of khat chewers met the Institute of Medicine’s recommendations for protein intake (10–35% of total energy).⁴² This finding underscores the need for improved consumption of animal-based meals among khat chewer women. Adequate protein intake is crucial for increasing muscle mass, as dietary amino acids are essential for the synthesis of hormones and enzymes, as well as for the development of the immune system.^{63 64}

Our study has also identified several micronutrient inadequacies among women that should be addressed by future interventions. Our findings reveal that, in khat chewer and non-chewer women, the median NAR for vitamin A, niacin, iron and vitamin B₁₂ was less than one. Consistent with the Bangladesh study, which highlighted significant deficiencies in essential micronutrients such as vitamin A and iron, our findings also emphasised similar nutrient inadequacies among women.⁶⁵ This suggests that the study population may be at risk of nutrient deficiencies for these essential vitamins and minerals. Iron deficiency has serious consequences on women of reproductive age, including increased risk of anaemia characterised by fatigue, reduced productivity and vulnerability to infection. Moreover, inadequate intake of iron during pregnancy may further lead to premature births, low birth weight and brain development problems with the child.⁶⁶ Treating iron deficiency in this group is also of paramount importance for the improvement of maternal and child health and the welfare of citizens.

The median MAR of 0.5 identified in this study highlights a significant issue of nutrient inadequacy, consistent with findings from St. Martin’s island in Bangladesh (0.43),⁶⁵ rural Bangladesh (0.49)⁶⁷ and India (0.54),⁶⁸ all indicating micronutrient inadequacy among women of reproductive age. The low MAR values highlight the urgent need for targeted interventions to promote dietary diversity and improve access to essential nutrients.

Notably, our findings revealed that more than three-quarters of both khat chewers and non-chewers had inadequate vitamin A intake. This may indicate low fruit and vegetable consumption in both groups. Vitamin A is crucial for maternal haemoglobin levels, embryonic growth and the development of organs and systems during pregnancy. Vitamin A deficiency is particularly prevalent among Ethiopian women⁶⁹ and can result in impaired vision (such as night blindness) and compromised immune function, as well as an increased risk of preterm delivery and infant mortality.⁷⁰

A greater proportion of khat chewers did not meet the EAR for vitamin B1. Inadequate intake of vitamin B₁ causes beriberi.⁷¹ Vitamin B1 deficiency in women of reproductive age can have significant health impacts, including an increased risk of complications during pregnancy and poor perinatal outcomes.⁷² Due to the immediate stimulating effects of khat, as well as its disruptive influence on sleep and mood, khat chewers often consume alcohol to counteract stimulation.⁷³ The concurrent use of khat and alcohol may exacerbate thiamine deficiency among khat chewers, as chronic alcohol consumption is known to contribute to thiamine deficiency through multiple mechanisms.⁷⁴

Our current study found that a significant number of women in both the khat chewer and non-chewer groups failed to meet the EAR for niacin, folate and vitamin B₁₂. However, the proportion of women not meeting the EAR for these nutrients is significantly higher among khat chewers compared with non-chewers. The prevalence of inadequate folate intake observed in this study was higher than that reported in a study conducted in the Oromia region (33%).⁷⁵ Folate is essential for women of reproductive age, as it supports DNA synthesis, cell division and helps prevent neural tube defects in the developing fetus during early pregnancy.⁷⁶ Vitamin B₁₂ deficiency in women of reproductive age can lead to several health problems such as anaemia, fatigue and neurological issues.^{77 78} During pregnancy, insufficient vitamin B₁₂ levels can increase the risk of neural tube defects.⁷⁸

Mineral inadequacies were also observed for calcium and zinc among the study sample, with a higher risk of inadequacy noted in the khat chewer group. The very low consumption of milk and milk products among women contributed to their low calcium intake. Calcium is an essential mineral that must be obtained from the diet.⁷⁹ A calcium-deficient diet can result in osteoporosis,⁸⁰ and is also implicated in other illnesses such as metabolic syndrome⁸¹ and cancer.⁸² The majority of women in our study, as well as those in comparable studies conducted in Ethiopia,^{83 84} had a low calcium intake and were thus at increased risk for these disorders.

The reduced intake of macronutrients and micronutrients among khat chewers compared with non-chewers may be due to the appetite suppression and increased metabolic rate effects of khat. Cathinone, the primary psychoactive component in khat, acts as a stimulant on the central nervous system. It increases the release of neurotransmitters such as dopamine and norepinephrine, resulting in heightened alertness, energy and euphoria. These effects can suppress appetite, similar to how other stimulants, such as amphetamines, reduce hunger.^{26 27 59} The increased dopamine and norepinephrine levels can also influence the brain’s reward and satiety centres, leading to reduced feelings of hunger. In addition to these central effects, cathinone also enhances sympathomimetic activity, which contributes to delayed gastric emptying.⁸⁵ Moreover, khat can increase metabolic rate, which may also contribute to a reduced desire to eat. The body’s energy expenditure increases, and this heightened metabolism might decrease the perceived need for food intake.¹⁹ Furthermore, the psychoactive effects of khat, including feelings of euphoria and stimulation, can distract from the sensation of hunger. Individuals using khat might become less concerned with eating, focusing more on the stimulant effects and social aspects of khat use.

Limitations of the study

We realise that our research has numerous possible limitations. First, the study was conducted at a single point in time and does not depict the dynamics of changes in women’s nutritional status and nutrient consumption. Second, self-reported khat chewing might be subject to measurement error. Because the study did not document particular patterns of khat use, such as number of sessions per week, hours per day/session, analysis of use intensity was limited. Third, biochemical markers that offer a full picture of nutrients were not measured. Lastly, nutrient intakes were not adjusted to get the usual intake distribution since only single-day intakes were obtained by 24-hour recall. However, a single 24-hour dietary recall per participant can be used to calculate the group average intake.⁸⁶ When data is collected from a large group, these individual variations tend to average out. This means that the mean intake calculated from a single 24-hour recall can provide a reasonable estimate of the group’s usual intake.

Implications of the study

Our study, which compares nutrient intake and nutritional status between khat chewer and non-chewer women of reproductive age, has substantial implications for policy, practice and research. The findings can guide the development of tailored nutritional guidelines for khat chewers, emphasising the need for increased intake of certain nutrients. Policymakers can integrate nutritional support into khat cessation programmes, recognising the role of proper nutrition in enhancing overall health and facilitating the quitting process. Understanding the differences in dietary patterns between khat chewers and non-chewers can help design more effective behavioural interventions that promote healthy eating habits among khat chewer women.

Routine nutritional assessments for khat chewers can become standard practice, allowing for early detection and intervention of nutrient deficiencies. Healthcare providers can offer personalised nutrition plans and supplements tailored to the specific needs of khat chewer women, improving their overall health outcomes.

Women of reproductive age may underuse critical reproductive health services because of stigma, poor health-seeking behaviour, fear of medical professionals’ judgement and the psychological or cognitive effects of chewing khat. This practice frequently results in missed or delayed access to these services, raising the possibility of reproductive health issues. Chewing khat can also have negative effects by escalating mental health problems and nutritional deficiencies. Collectively, these factors place additional strain on already limited reproductive health resources, particularly in low-income settings.

Research can further explore how khat chewing affects nutrient absorption and metabolism in women, shedding light on gender-specific biological mechanisms. Longitudinal studies can track changes in nutritional status over time in khat chewers versus non-chewers, establishing causal relationships and long-term health impacts. Additionally, future studies can evaluate the effectiveness of innovative nutritional interventions in khat chewing cessation programmes, providing evidence for best practices.

Conclusions and recommendations

In conclusion, our results highlight that khat chewers had lower BMI, poorer dietary diversity and inadequate intake of most nutrients compared with non-chewer women. Women who chewed khat were more likely to have inadequate intake of carbohydrate, protein, thiamine, riboflavin, niacin, vitamin B₁₂, zinc and calcium than their counterparts. Public health programmes aiming to improve nutritional status should develop strategies to address the spread of khat chewing.

Screening for khat use in all women of reproductive age, as part of preconception health promotion, and referral to substance abuse facilities for those women found to have a khat use problem should become the standard of care in all healthcare facilities. These findings may have implications for antisubstance abuse programmes, which are a priority in most public health programmes. Such programmes should integrate nutrition interventions to address the dual burden of substance use and undernutrition.

Additionally, khat marketing and promotion targeting women of reproductive age should be strictly monitored by governments. Future longitudinal studies are needed to assess changes in food consumption, body weight and BMI among khat-chewing women. Further research should also explore the effects of concurrent khat and other substance use on women’s nutritional status and nutrient intake using biochemical indicators.

Data availability statement

Data are available upon reasonable request.