Sports injuries among male futsal players in Herat, Afghanistan: a cross-sectional study

Abstract

Background

Futsal involves repeated high-intensity movements, rapid direction changes, and frequent player contact, all of which may contribute to injury risk. Evidence on futsal-related injuries from low-resource and post-conflict settings remains limited. This study aimed to describe the epidemiology and correlates of self-reported futsal-related injuries among male league players in Herat, Afghanistan.

Methods

A descriptive cross-sectional study was conducted among 229 active male futsal players registered in the Premier League and First Division leagues in Herat. Participants were recruited using an attempted census of accessible eligible players from participating teams. Data were collected using a structured self-administered questionnaire covering sociodemographic characteristics, anthropometry, lifestyle, nutrition, sleep, training characteristics, FIFA 11 + use/awareness, and career/lifetime futsal-related injury history. Injury was defined as any physical complaint sustained during futsal training or match play. Descriptive statistics, chi-square tests, and binary logistic regression were used to examine exploratory associations with injury history.

Results

Overall, 207 players reported at least one career/lifetime futsal-related injury, yielding a prevalence of 90.4%. Injuries most commonly involved the ankle (48.0%) and knee (32.3%); ankle sprain was the leading injury type (55.9%). Most injuries occurred during matches (75.1%) and were mainly attributed to opponent contact (55.0%) and unsuitable venues (26.6%). In bivariate analysis, injury history was associated with age (p = 0.002), marital status (p = 0.002), economic status (p = 0.007), employment status (p = 0.032), and weekly training frequency (p = 0.012). In exploratory adjusted analyses, higher odds of reported injury history were observed for age 25–34 years (OR = 9.519, p = 0.032), good/very good economic status (OR = 31.284, p = 0.014), evening training (OR = 5.772, p = 0.049), and venues reported as only sometimes suitable (OR = 3.492, p = 0.047).

Conclusion

This study provides the first epidemiological description of self-reported futsal-related injuries among male league players in Herat, Afghanistan. The findings indicate a high reported burden of injury, especially involving the lower limb, and suggest that injury-prevention strategies should prioritize player education, safer and more consistent playing environments, and prospective injury surveillance. Adjusted associations should be interpreted cautiously because of the cross-sectional design, lifetime injury recall, and sparse non-injury events.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13102-026-01791-w.

Introduction

Futsal, a high-intensity indoor variant of association football, is characterized by repeated sprinting, rapid acceleration and deceleration, frequent changes of direction, pivoting, jumping, and close player contact. These physical and tactical demands require substantial intermittent endurance, muscular power, agility, and aerobic capacity [1, 2].

They also create a distinct injury profile, particularly affecting the lower extremities. Previous futsal injury studies have consistently identified the ankle, knee, and thigh as common injury sites, with sprains, contusions, muscle injuries, and ligament injuries frequently reported [3, 4]. In addition to sport-specific demands, musculoskeletal injury burden has also been examined in occupational and applied contexts, emphasizing the role of environmental and socioeconomic determinants in injury risk [5].

Although the epidemiology of futsal injuries is increasingly documented, most available evidence derives from professional or semi-professional settings in higher-resource countries. Reported injury incidence varies considerably across competitive contexts, with some studies indicating rates that exceed those observed in traditional outdoor football [4]. However, injury patterns and prevention needs may differ substantially in low-resource and post-conflict settings, where playing surfaces, access to protective equipment, medical support, rehabilitation services, nutrition, and awareness of injury-prevention programmes may be limited. In Afghanistan, futsal is widely played, yet systematic epidemiological data on futsal-related injuries remain scarce, limiting the ability of coaches, clubs, clinicians, and sports authorities to design context-appropriate prevention strategies.

The etiology of futsal injuries is multifactorial and reflects the interaction of intrinsic and extrinsic risk factors. Player-related factors such as age, previous injury history, muscle weakness, neuromuscular imbalance, inadequate nutrition, and insufficient or poor-quality sleep may increase susceptibility to injury [6, 7]. Extrinsic factors include direct player-to-player contact, training load, playing-surface characteristics, and the availability or implementation of structured injury-prevention strategies, including neuromuscular warm-up programmes such as FIFA 11+ [3, 8]. These determinants may be especially relevant in settings where formal injury surveillance and sports medicine support are limited.

Herat provides an important setting for examining futsal injuries because organized leagues operate within a context of constrained sports medicine infrastructure and limited formal injury monitoring. Understanding the burden and pattern of injuries among active league players can provide an initial evidence base for future prevention programmes and prospective surveillance. Therefore, this study aimed to estimate the self-reported career/lifetime prevalence of futsal-related injuries and describe their anatomical distribution, type, mechanism, timing, and treatment patterns among male Premier League and First Division futsal players in Herat, Afghanistan. A secondary objective was to explore sociodemographic, anthropometric, lifestyle, nutrition, sleep, and training-related correlates of injury history.

Therefore, this study was designed to address this critical knowledge gap. The primary aim of this research was to determine the prevalence of sports injuries and identify their associated factors among male futsal players competing in the Premier League and First Division of Herat, Afghanistan. The specific objectives were threefold: first, to describe the sociodemographic, lifestyle, nutritional, and training characteristics of this athletic population; second, to determine the prevalence, anatomical location, type, and mechanism of self-reported injuries; and third, to identify key factors that are significantly associated with a player’s history of having sustained an injury. By providing the first comprehensive epidemiological profile of this understudied population, this study seeks to generate crucial evidence to inform targeted injury prevention strategies and promote safer sports participation. In addition to estimating injury prevalence, the study examined sociodemographic, anthropometric, lifestyle, nutrition, sleep, and training-related variables as exploratory correlates that may help identify priorities for future injury-prevention planning in this low-resource sports setting.

Methodology

Study design and setting

A descriptive, cross-sectional study design was employed to investigate the prevalence and correlates of sports injuries among futsal players. The research was conducted in Herat, a major urban center in western Afghanistan. Data collection took place at various indoor gymnasiums and sports venues across the city that host the official matches and training sessions for the provincial futsal leagues. This setting provided direct access to the target population in their natural sporting environment. The study was initiated and conducted by researchers affiliated with the Faculty of Medicine at Ghalib University in Herat.

Data were collected from multiple futsal clubs/teams and indoor venues used for official training sessions and league matches in Herat. Because the study used an attempted census of accessible players, the recruitment frame consisted of teams and venues that were available to the research team during the data-collection period.

Participants and sampling strategy

The target population comprised active male futsal players registered with teams competing in the Premier League and First Division of Herat province during the data-collection period. Because no previous epidemiological data on futsal injuries were available from Afghanistan, the study was designed as an exploratory cross-sectional survey using an attempted census of all accessible eligible players from participating teams rather than probability-based sampling. All available players attending official training sessions or matches during the study period were invited to participate.

Because the study was descriptive and exploratory, the sample-size justification was based on feasibility and estimation precision rather than hypothesis-testing power. The findings should therefore be interpreted as descriptive and hypothesis-generating rather than definitive evidence of independent risk prediction.

The inclusion criteria were: (1) male futsal player registered with a Premier League or First Division team in Herat province; (2) active participation in team training or competition during the study period; (3) ability to understand and complete the Persian/Dari questionnaire; and (4) provision of informed consent. Players were excluded if they were not registered with a Herat Premier League or First Division team, were outside Herat province during data collection, declined participation, or submitted incomplete questionnaires that prevented classification of injury status. Players with a previous injury or those who had returned to play after injury were not excluded, because the purpose of the study was to estimate self-reported futsal injury history among active players. However, players who were not present because of a severe current injury may have been missed, and this potential selection bias is acknowledged as a limitation.

Sample size justification

A formal a priori sample-size calculation was not performed because the study was exploratory and no prior local estimates of futsal injury prevalence were available from Afghanistan. Instead, the recruitment strategy aimed to include the maximum feasible number of eligible players from the accessible Premier League and First Division teams in Herat. The final sample of 229 players provides acceptable precision for estimating injury prevalence in this setting. Using the observed prevalence of 90.4%, the approximate 95% confidence interval for the main prevalence estimate is narrow enough to support descriptive epidemiological interpretation. Nevertheless, because convenience-based recruitment was used, the sample should not be interpreted as fully representative of all futsal players in Afghanistan.

Data collection instrument and procedure

Data were gathered using a structured, self-administered questionnaire developed by the research team specifically for this study, informed by an extensive review of the relevant literature. The instrument was initially developed in Persian (the local language) to ensure clarity and comprehension among participants. The questionnaire was developed in Persian/Dari for participant administration. The English version was prepared for reporting and supplementary submission. Because a formal forward–backward translation procedure was not conducted, minor translation-related differences in wording may be possible; this limitation has been acknowledged. An English-language version of the questionnaire has been provided as Supplementary File 1. The questionnaire was divided into four distinct sections designed to capture a comprehensive range of potential risk factors and injury characteristics:

• Sect.  1: General Characteristics: This section collected sociodemographic data, including age, weight (kg), height (cm), marital status, highest level of education, economic status (self-rated), and current employment status. Body mass index was calculated as weight in kilograms divided by height in meters squared. BMI was categorized according to standard adult categories where appropriate. Because BMI does not distinguish fat mass from lean mass, particularly in athletic populations, it was interpreted only as a general anthropometric indicator and not as a measure of body composition. It also inquired about lifestyle factors such as tobacco use and participation in other sports alongside futsal.

• Sect.  2: Nutrition and Sleep: This part focused on dietary and recovery habits. It included questions on adherence to special diets, daily fluid intake, consumption of energy drinks and carbonated beverages, daily meal frequency, use of nutritional supplements, and specific types of food consumed post-exercise. Sleep patterns were also assessed, including average nightly sleep duration and sleep habits before a match.

• Sect.  3: Training and Competition: This section gathered information related to sports-specific activities, such as weekly training frequency, duration of each session, typical time of day for training, length of the preseason preparation period, and the number of games played per week. It also specifically asked about the use of and awareness of the FIFA 11 + injury prevention program and the player’s primary playing position.

• Sect.  4: Injury History: The final section was dedicated to the player’s experience with sports injuries. It began with a dichotomous question about whether the player had ever sustained an injury while playing futsal. For those who responded affirmatively, subsequent questions explored the context of the injury (match, warm-up, or training), the use of protective equipment, the anatomical location of the injury, the specific type of injury (e.g., sprain, fracture), the mechanism of injury (e.g., contact with opponent, body rotation), and the type of treatment sought (e.g., specialist, local healer, physiotherapy).

The questionnaire was reviewed by sports medicine, epidemiology, and clinical faculty members for content relevance, clarity, and cultural appropriateness. A small pilot test was conducted among 30 futsal players who were not included in the final analysis to assess comprehension, wording, and completion time. Minor wording modifications were made before data collection. Because most questionnaire items were factual, categorical, or checklist-based rather than items measuring a single latent construct, internal consistency testing using Cronbach’s alpha was not considered appropriate for the full instrument.

The research team, led by the principal investigator from Ghalib University, administered the questionnaires directly to the players at their respective training and competition venues. The purpose of the study was explained to all potential participants, and verbal consent was obtained prior to their completion of the questionnaire. The process was designed to be anonymous and confidential to encourage honest and accurate responses.

Definition of variables and outcomes

The primary outcome was self-reported career/lifetime prevalence of futsal-related injury among currently active players. Participants were asked whether they had ever sustained an injury while playing futsal. Therefore, the outcome reflects cumulative injury history rather than incident injury during a defined follow-up period. An injury was defined in accordance with the international consensus statement on injury surveillance in football as “any physical complaint sustained by a player that resulted from a futsal match or futsal training, irrespective of the need for medical attention or time loss from futsal activities”.⁴ This broad definition was chosen to capture the full spectrum of physical complaints experienced by the players. The independent variables included all sociodemographic, lifestyle, nutritional, and training characteristics collected through the questionnaire. These were treated as categorical variables for the purpose of analysis. For example, age was categorized into three groups: 14–20, 21–24, and 25–34 years, and economic status was self-rated on a five-point scale (Very Poor to Very Good). Recent research has also emphasized the importance of neuromuscular and motor control factors in understanding injury mechanisms and movement-related risks [9].

Age, weight, height, and BMI were categorized during analysis for descriptive clarity and to allow cross-tabulation with injury history. We acknowledge that categorizing continuous variables may reduce statistical power and obscure dose-response patterns. Therefore, these analyses should be interpreted as exploratory. Future studies with larger samples should retain continuous exposure variables where possible and model non-linear associations appropriately.

Because the study was cross-sectional, all independent variables were measured at the time of survey. Accordingly, variables such as current marital status, economic status, training habits, and use of preventive programs may not necessarily reflect the player’s status at the exact time an earlier injury occurred. For this reason, the analyses were interpreted as associations with injury history rather than causal risk factors. Terms such as ‘predictor’ and ‘determinant’ were avoided unless supported by temporal evidence.

Statistical analysis

Data were coded, entered, and analyzed using SPSS version 27. Descriptive statistics were used to summarize participant characteristics, training habits, lifestyle factors, and injury patterns. Categorical variables were presented as frequencies and percentages. Continuous variables, where applicable, were summarized using means and standard deviations. Questionnaires were reviewed for completeness before analysis. Participants with missing injury-status information were excluded because the primary outcome could not be classified. For other variables, analyses were conducted using available complete data for each variable. Variable-specific denominators were checked, and no imputation was performed because the study was descriptive and exploratory.

Bivariate associations between categorical independent variables and self-reported injury history were examined using Pearson’s chi-square test. Expected cell counts were checked for each comparison, and Fisher’s exact test was used where chi-square assumptions were not met. For variables with more than two categories and small expected cell counts, the Fisher-Freeman-Halton exact test was applied. Binary logistic regression was used to estimate adjusted odds ratios and 95% confidence intervals for selected sociodemographic and training-related variables. Variables were selected based on clinical relevance, contextual importance, and previous injury literature rather than automated stepwise selection. Selected variables were entered simultaneously within each model. Before interpretation, the models were assessed for sparse categories, unstable estimates, and wide confidence intervals. Because the outcome was common and highly imbalanced, the adjusted odds ratios were interpreted cautiously and were not considered direct estimates of risk.

The regression models were considered exploratory because of the high outcome prevalence, small number of non-injured participants, and wide confidence intervals. The small number of non-events limited the number of variables that could be reliably modeled and increased the risk of sparse-data bias, overfitting, and unstable odds-ratio estimates. Therefore, adjusted odds ratios were interpreted cautiously as hypothesis-generating measures of association rather than as definitive evidence of independent prediction.

No formal correction for multiple comparisons was applied because the analysis was exploratory and hypothesis-generating. Therefore, findings were interpreted using the magnitude and direction of associations, 95% CIs, consistency with prior literature, and biological or contextual plausibility rather than p-values alone. A p-value < 0.05 was considered statistically significant.

Results

A total of 229 male futsal players from the Premier League and First Division in Herat participated in the study. The sociodemographic profile of the cohort is detailed in Table 1. The participants were primarily distributed across the older age brackets, with 42.4% in the 21–24 age group and 42.8% in the 25–34 age group. The majority of players had a height between 166 and 180 cm (80.8%) and a weight between 61 and 80 kg (78.6%). Regarding BMI, the mean BMI of participants was 23.4 ± 3.21 kg/m², 76.9% of the participants were classified as underweight or normal weight (BMI < 25.0), while 23.1% were categorized as overweight or obese (BMI > = 25.0). A majority of the players were married (59.4%). In terms of education, the largest group had completed high school (41.0%), followed by those with a bachelor’s degree or higher (31.4%). Over half of the participants were self-employed (51.5%), while 22.7% were students. When analyzed in three categories, the self-reported economic status was moderate for 50.2% of the players, while 31.4% reported a good or very good status. Participation in other sports was high, with 50.2% of the cohort playing football and 45.9% engaged in bodybuilding. A notable portion of the athletes (35.4%) reported using tobacco.

Table 1.

Demographic and general characteristics of the participants

		Count	%
Age (Years)	14–20 years	34	14.8
	21–24 years	97	42.4
	25–34 years	98	42.8
Weight (Kg)	22–60 kg	28	12.2
	61–80 kg	180	78.6
	81 kg and above	21	9.2
Height (cm)	143–165 cm	23	10.0
	166–180 cm	185	80.8
	181 cm and above	21	9.2
BMI	Underweight/normal (< 25.0)	176	76.9
	Overweight/obese ( > = 25.0)	53	23.1
Marital Status	Single	93	40.6
	Married	136	59.4
Education Level	Illiterate	14	6.1
	Elementary	21	9.2
	Intermediate	28	12.2
	High School	94	41.0
	Bachelor’s and above	72	31.4
Economic status in 3 categories	Poor/Very Poor	42	18.3
	Moderate	115	50.2
	Good/Very Good	72	31.4
Employment status in 4 categories	Unemployed	20	8.7
	Self-employed	118	51.5
	Student	52	22.7
	Employee/Other	39	17.0
Other sport	Body building	105	45.9
	Football	115	50.2
	No	9	3.9
Tobacco Use	Yes	81	35.4
	No	148	64.6

Table 2 presents the data on the players’ dietary habits, sleep patterns, and general health. The vast majority of players (86.9%) reported not following any special diet, and an even larger proportion (96.1%) did not take nutritional supplements. The consumption of energy drinks was extremely common, with 90.8% of players reporting their use. Most players (60.3%) consumed 1–2 L of fluid daily. Regarding meal frequency, two-thirds of the athletes (67.7%) consumed three meals per day. Post-exercise nutritional practices appeared to be suboptimal, with very few players reporting consumption of carbohydrates (3.9%), proteins (4.8%), or fats (10.9%) after training or matches; fruit was consumed by 16.6%. Sleep patterns were varied: 38.0% reported sleeping 8 h per night, while a significant portion reported irregular sleep (24.5%). Critically, over half of the players (52.4%) slept less than 8 h before a match.

Table 2.

Dietary habits, fluid intake, supplement use, and sleep patterns of the participants

		N	%			N	%
Following Special Diet	Yes	30	13.1	Foods After Exercise (Carbohydrate)	Yes	9	3.9
	No	199	86.9		No	220	96.1
Daily Fluid Intake	Less than 1 L	58	25.3	Foods After Exercise (Proteins)	Yes	11	4.8
	1–2 L	138	60.3		No	218	95.2
	More than 3 L	33	14.4	Foods After Exercise (Fat)	Yes	25	10.9
Consuming Energy Drinks	Yes	208	90.8		No	204	89.1
	No	21	9.2	Foods After Exercise (Fruit)	Yes	38	16.6
Carbonated Drink Consumption	250 cc	122	53.3		No	191	83.4
	500 cc	87	38.0	Food after exercise (Energy Drinks)	Less one hour	34	14.8
	1000 cc	11	4.8		One to two hour	163	71.2
	More than 1000 cc	9	3.9		After two hour	32	14.0
Daily Meal Frequency	One meal	17	7.4	Sleep	8 h	87	38.0
	Two meals	34	14.8		Less than 6 h	24	10.5
	Three meals	155	67.7		More than 8 h	59	25.8
	More than three meals	23	10.0		Irregular sleep	56	24.5
Takes Supplements	Yes	9	3.9		Sleep during day time	3	1.3
	No	220	96.1	Sleep before match	Less than 8 h	120	52.4
Has Illness	Yes	6	2.6		More than 8 h	62	27.1
	No	223	97.4		Irregular	47	20.5

As shown in Table 3, the most common training frequencies were thrice (43.2%) and twice (38.4%) per week. The vast majority of training sessions (85.2%) lasted for one hour. Afternoon was the preferred time for training for 51.1% of the players. Regarding injury prevention programs, the data revealed a significant gap: 38.9% of players did not use the FIFA 11 program, and an additional 23.6% were unaware of its existence. Most players (50.7%) had a preseason preparation period of 3 to 6 weeks. In terms of playing position, the sample was relatively evenly distributed among defenders (30.6%), midfielders (27.9%), forwards (22.7%), and goalkeepers (18.8%).

Table 3.

Training frequency, duration, timing, and game-related characteristics of the participants

		N	%			N	%
Weekly Training Frequency	Once	20	8.7	Preseason Duration	Less than 3 weeks	19	8.3
	Twice	88	38.4		3 to 6 weeks	116	50.7
	Thrice	99	43.2		More than 6 weeks	94	41.0
	Irregular	22	9.6	Weekly Games Played	One game	64	27.9
Training Duration	Less than 1 h	12	5.2		Two games	102	44.5
	1 h	195	85.2		Three games	63	27.5
	More than 1 h	22	9.6	Suitable Venue for Games	Yes	42	18.3
Training Time	Morning	9	3.9		No	23	10.0
	Afternoon	117	51.1		Sometimes	164	71.6
	Evening	72	31.4	Playing Position	Goalkeeper	43	18.8
	Varies	31	13.5		Defender	70	30.6
FIFA 11 Program Used	Yes	86	37.6		Midfielder	64	27.9
	No	89	38.9		Forward	52	22.7
	Unaware of FIFA 11	54	23.6

The prevalence of self-reported injuries was exceptionally high, with 207 out of 229 players (90.4%) reporting having experienced at least one injury during their futsal career (Table 4). The lower limbs were the most frequently injured body region, with the ankle being the most common site of injury (48.0%), followed by the knee (32.3%). The single most reported type of injury was an ankle sprain, experienced by 55.9% of the players. Contusions (33.6%) and knee ligament tears (18.8%) were also common. The primary reported cause of injury was contact with an opponent (55.0%), followed by playing on an unsuitable venue (26.6%). Most injuries occurred during a match (75.1%). Regarding treatment, a majority (69.4%) sought care from a specialist, but a substantial proportion also consulted a local/traditional healer (31.4%) or used home remedies (15.3%).

Table 4.

Injury prevalence, types, causes, timing, protective equipment use, affected body parts, and treatment approaches among participants

	N	%		N	%		N	%
Experienced Injury	207	90.4	Type of Injury (Ankle sprain)	128	55.9	Injury Time (Match)	172	75.1
Upper limb injury (Shoulder)	31	13.5	Type of Injury (Knee ligament tear)	43	18.8	Injury Time (Warm-up)	29	12.7
Upper limb injury (Arm)	24	10.5	Type of Injury (Hamstring injury)	9	3.9	Injury Time (Exercise)	41	17.9
Upper limb injury (Elbow)	39	17	Type of Injury (Fracture)	37	16.2	Protective equipment (Shin Brace)	75	40.1
Upper limb injury (Forearm)	22	9.6	Type of Injury (Contusion)	77	33.6	Protective equipment (Ankle Brace)	36	21.1
Upper limb injury (Wrist)	70	30.8	Type of Injury (Other injury type)	32	14	Protective equipment (Wrist Brace)	89	48.4
Upper limb injury (Fingers)	20	8.7	Cause of Injury (Contact with opponents)	126	55	Protective equipment (Knee Brace)	37	16.2
Lower limb injury (Pelvic)	13	5.7	Cause of Injury (Incorrect landing)	47	20.5	Protective equipment (Others)	12	5.2
Lower limb injury (Thigh)	29	12.7	Cause of Injury (Unsuitable Venue)	61	26.6	Injured Body Part (Ankle)	64	27.9
Lower limb injury (Knee)	74	32.3	Cause of Injury (Exercise)	42	18.3	Injured Body Part (Knee)	29	12.7
Lower limb injury (Leg)	33	14.4	Cause of Injury (Without warm-up)	27	11.8	Injured Body Part (Thigh)	9	3.9
Lower limb injury (Ankle)	110	48	Muscle Injury Type (Muscle cramp)	163	71.5	Injured Body Part (Back)	14	6.1
Lower limb injury (Finger)	9	3.9	Muscle Injury Type (Muscle contusion)	130	56.8	Injured Body Part (Head)	5	2.2
Injury Situation (Fast running)	74	32.3	Muscle Injury Type (Muscle sprain)	23	10	Injured Body Part (Shoulder)	5	2.2
Injury Situation (Sudden stop)	55	24	Muscle Injury Type (Muscle bruise)	79	34.5	Injured Body Part (Wrist)	12	5.2
Injury Situation (Body rotation)	99	43.2	Muscle Injury Type (Muscle tear)	36	15.7	Injured Body Part (Pelvic)	3	1.3
Injury Situation (Body stretch)	37	16.2	Head Injury Type (Skull)	32	14	Injured Body Part (Elbow)	11	4.8
Injury Situation (Ball impact)	28	12.3	Head Injury Type (Eye)	26	12.1	Treatment (Specialist)	159	69.4
Injury Situation (others)	14	6.1	Head Injury Type (Nose)	32	15.1	Treatment (Local)	72	31.4
			Head Injury Type (Jaw)	16	7.6	Treatment (Home)	35	15.3
			Head Injury Type (Cheek)	13	5.8	Treatment (Physiotherapy)	40	17.5

Because the outcome represents self-reported career/lifetime injury history, the following associations should be interpreted as exploratory correlates of having ever experienced a futsal-related injury, not as evidence that the measured characteristics caused the injury. The results of the bivariate analysis, presented in Table 5, identified four sociodemographic variables that were significantly associated with a history of injury. A player’s age group (p = 0.002), marital status (p = 0.002), self-reported economic status (p = 0.007), and employment status (p = 0.032) were significantly associated with injury history. Specifically, injury prevalence increased with age, reaching 96.9% in the 25–34 years group. While a high percentage of both marital-status groups reported injuries, single players had a higher prevalence (97.8%) than married players (85.3%). In terms of economic strata, those with good/very good status reported the highest prevalence (98.6%). Regarding employment, self-employed players (94.1%) and employee/other players (94.9%) showed higher injury rates than students or unemployed players. In contrast, no significant associations were found between injury experience and weight, height, BMI, education level, participation in other sports, or tobacco use.

Table 5.

Bivariate associations between sociodemographic characteristics and self-reported injury history

Variable	Option	Experienced injury: Yes n (%)	Test used	Test statistic	P-value
Age (Years)	14–20 years	26 (76.5)	Fisher’s exact	—	0.002*
	21–24 years	86 (88.7)
	25–34 years	95 (96.9)
Weight (Kg)	22–60 kg	24 (85.7)	Fisher’s exact	—	0.559
	61–80 kg	164 (91.1)
	81 kg and above	19 (90.5)
Height (cm)	143–165 cm	19 (82.6)	Fisher’s exact	—	0.427
	166–180 cm	169 (91.4)
	181 cm and above	19 (90.5)
BMI	Underweight/normal	159 (90.3)	Pearson chi-square	0.002	0.961
	Overweight/obese	48 (90.6)
Marital Status	Single	91 (97.8)	Pearson chi-square	10.026	0.002*
	Married	116 (85.3)
Education Level	Illiterate	12 (85.7)	Fisher’s exact	—	0.232
	Elementary	19 (90.5)
	Intermediate	26 (92.9)
	High School	81 (86.2)
	Bachelor’s +	69 (95.8)
Economic Status	Poor/Very Poor	36 (85.7)	Fisher’s exact	—	0.007*
	Moderate	100 (87.0)
	Good/Very Good	71 (98.6)
Employment	Unemployed	16 (80.0)	Fisher’s exact	—	0.032*
	Self-employed	111 (94.1)
	Student	43 (82.7)
	Employee/Other	37 (94.9)
Other sport	Body building	94 (89.5)	Fisher’s exact	—	0.791
	Football	105 (91.3)
	No	8 (88.9)
Tobacco Use	Yes	76 (93.8)	Pearson chi-square	1.702	0.192
	No	131 (88.5)

*P < 0.05. Fisher’s exact test was used where expected cell counts were small. For variables with more than two categories, the Fisher-Freeman-Halton exact test was applied

To further investigate the relationship between sociodemographic factors and injury history while controlling for confounding, a binary logistic regression model was employed (Table 6). In the adjusted model, age and economic status showed statistically significant associations with self-reported injury history. Compared with players aged 14–20 years, those aged 25–34 years had significantly higher odds of reporting injury history (p = 0.032, aOR = 9.519, 95% CI: 1.215–74.605). In addition, players reporting good/very good economic status had substantially higher odds of injury history compared with those reporting poor/very poor economic status (p = 0.014, aOR = 31.284, 95% CI: 2.026–483.026), whereas the moderate economic status category was not statistically significant. However, these results should be interpreted cautiously because the outcome was highly imbalanced. Only 22 participants were classified as non-injured, resulting in limited non-events for multivariable modeling and wide confidence intervals for several estimates. Therefore, Table 6 is presented as an exploratory adjusted analysis rather than a definitive prediction model.

Table 6.

Adjusted associations between sociodemographic characteristics and self-reported injury history

Variables		p-value	OR	95% C.I.for OR
				Lower	Upper
Age (Years)	14–20 years (ref)	0.077
	21–24 years	0.082	3.001	0.869	10.366
	25–34 years	0.032	9.519	1.215	74.605
Weight (Kg)	81 kg and above (ref)	0.649
	22–60 kg	0.680	1.946	0.082	46.182
	61–80 kg	0.438	2.838	0.203	39.661
Height (cm)	181 cm and above (ref)	0.197
	143–165 cm	0.153	6.450	0.499	83.318
	166–180 cm	0.072	6.342	0.850	47.334
BMI	Overweight/obese (ref)
	Underweight/normal	0.653	1.489	0.263	8.444
Marital Status	Married (ref)
	Single	0.087	5.495	0.782	38.592
Education Level	Bachelor’s + (ref)	0.625
	Illiterate	0.248	0.271	0.030	2.484
	Elementary	0.917	1.134	0.106	12.133
	Intermediate	0.841	1.252	0.139	11.236
	High School	0.434	0.517	0.099	2.703
Economic status	Poor/Very Poor (ref)	0.034
	Moderate	0.836	1.162	0.279	4.834
	Good/Very Good	0.014	31.284	2.026	483.026
Employment status	Employee/Other (ref)	0.749
	Unemployed	0.848	0.805	0.088	7.328
	Self-employed	0.941	1.077	0.152	7.633
	Student	0.524	0.519	0.069	3.898
Other sport	No (ref)	0.253
	Body building	0.732	1.718	0.078	38.021
	Football	0.381	3.968	0.182	86.730
Tobacco Use	Yes (ref)
	No	0.197	2.602	0.608	11.134
	Constant	0.097	0.024

The association between training-related variables and injury history is presented in Table 7. Bivariate analysis showed that weekly training frequency was significantly associated with injury experience (p = 0.012). Players who trained three times per week or irregularly reported a higher prevalence of injury (95.0%) compared with those training once or twice per week (85.2%). Other training factors, including training duration, training time, FIFA 11 + program use/awareness, preseason duration, number of weekly games, venue suitability, and playing position, were not significantly associated with injury history in bivariate analysis.

Table 7.

Bivariate associations between training characteristics and self-reported injury history

Variable	Option	Experienced injury: Yes n (%)	Test used	Test statistic	P-value
Weekly Training Frequency	Once or Twice	92 (85.2)	Pearson chi-square	6.384	0.012*
	Thrice or Irregular	115 (95.0)
Training Duration	Less than 1 h	10 (83.3)	Fisher’s exact	—	0.422
	1 h	176 (90.3)
	More than 1 h	21 (95.5)
Training Time	Morning	8 (88.9)	Fisher’s exact	—	0.416
	Afternoon	104 (88.9)
	Evening	68 (94.4)
	Varies	27 (87.1)
FIFA 11 Program Used	Yes	73 (84.9)	Pearson chi-square	4.868	0.088
	No	83 (93.3)
	Unaware of FIFA 11	51 (94.4)
Preseason Duration	Less than 3 weeks	16 (84.2)	Fisher’s exact	—	0.459
	3 to 6 weeks	104 (89.7)
	More than 6 weeks	87 (92.6)
Weekly Games Played	One game	55 (85.9)	Pearson chi-square	3.171	0.205
	Two games	92 (90.2)
	Three games	60 (95.2)
Suitable Venue	Yes	35 (83.3)	Fisher’s exact	—	0.216
	No	22 (95.7)
	Sometimes	150 (91.5)
Playing Position	Goalkeeper	38 (88.4)	Fisher’s exact	—	0.583
	Defender	66 (94.3)
	Midfielder	57 (89.1)
	Forward	46 (88.5)

*P < 0.05. Fisher’s exact test was used where expected cell counts were small. For variables with more than two categories, the Fisher-Freeman-Halton exact test was applied

When training characteristics were analyzed using binary logistic regression (Table 8), training time and venue suitability showed statistically significant adjusted associations with self-reported injury history. Players who trained in the evening had significantly higher adjusted odds of injury history compared with those whose training time varied (p = 0.049, aOR = 5.772, 95% CI: 1.011–32.967). In addition, players who reported that venues were only sometimes suitable had higher adjusted odds of injury history compared with those reporting consistently suitable venues (p = 0.047, aOR = 3.492, 95% CI: 1.017–11.989). Weekly training frequency, training duration, FIFA 11 + use/awareness, preseason duration, weekly games played, and playing position did not maintain statistical significance in the adjusted model.

Table 8.

Adjusted associations between training characteristics and self-reported injury history

Variables		p-value	OR	95% C.I.for OR
				Lower	Upper
Weekly Training Frequency	Once or Twice (ref)
	Thrice or Irregular	0.136	2.612	0.739	9.234
Training Duration	Less than 1 h (ref)	0.824
	1 h	0.873	1.171	0.168	8.179
	More than 1 h	0.570	2.314	0.128	41.915
Training Time	Varies (ref)	0.219
	Morning	0.766	1.528	0.093	25.010
	Afternoon	0.367	2.058	0.429	9.867
	Evening	0.049	5.772	1.011	32.967
FIFA 11 Program Used	Unaware of FIFA 11 (ref)	0.192
	Yes	0.443	0.469	0.068	3.244
	No	0.604	1.653	0.247	11.082
Preseason Duration	Less than 3 weeks (ref)	0.573
	3 to 6 weeks	0.315	2.735	0.385	19.436
	More than 6 weeks	0.311	2.830	0.378	21.160
Weekly Games Played	One game (ref)	0.367
	Two games	0.937	1.047	0.335	3.266
	Three games	0.198	2.987	0.564	15.825
Suitable Venue for Games	Yes (ref)	0.134
	No	0.326	3.325	0.303	36.537
	Sometimes	0.047	3.492	1.017	11.989
Playing Position	Forward (ref)	0.609
	Goalkeeper	0.726	1.284	0.318	5.191
	Defender	0.334	2.034	0.482	8.571
	Midfielder	0.697	0.780	0.223	2.724
	Constant	0.402	0.284

Discussion

This study provides one of the first epidemiological descriptions of self-reported futsal-related injuries among male league players in Herat, Afghanistan. The principal finding was a very high lifetime prevalence of injury: 90.4% of players reported at least one futsal-related injury during their playing career. The dominant injury pattern involved the lower limb, particularly the ankle and knee, with ankle sprain being the most frequently reported injury type. Most injuries occurred during matches and were commonly attributed to contact with an opponent. In addition to these globally recognizable futsal injury patterns, several findings were particularly context-specific: very high energy drink consumption, limited use or awareness of FIFA 11+, frequent reports of unsuitable venues, and substantial use of local/traditional healers or home remedies. Together, these findings suggest that injury prevention in this setting should not be limited to player-level conditioning alone but should also address infrastructure, health education, access to evidence-based care, and culturally embedded treatment pathways.

The high reported injury prevalence should be interpreted carefully because this study measured career/lifetime injury history rather than prospective injury incidence. Direct comparison with prospective studies is therefore limited. In elite male futsal players in Portugal, Lopes et al. prospectively followed 167 players over an 8-month season and found that 67.6% sustained a time-loss injury, with an overall incidence of 4.5 injuries per 1000 h of exposure and match incidence approximately nine times higher than training incidence [10]. Similarly, prospective studies in female futsal have reported substantial injury risk, but with season-based incidence rather than lifetime prevalence: Lago-Fuentes et al. reported that 60.6% of elite female players sustained an injury during one season, while Ruiz-Pérez et al. reported 6.7 injuries per 1000 h over three seasons in sub-elite female players [11, 12]. The higher prevalence in the present study may therefore reflect the cumulative nature of the outcome, a broad “any physical complaint” injury definition, possible recall of minor injuries over many years, and potential differences in playing conditions and medical support. Thus, the key implication is not that Herat players necessarily have a higher incidence than all other futsal populations, but that the self-reported lifetime burden of injury is substantial enough to justify organized prevention and surveillance.

The anatomical distribution of injuries was broadly consistent with international futsal literature. A systematic review of futsal injuries concluded that the lower limb is the main injured region, especially the knee and ankle, and that prevention should consider player equipment, playing facilities, rules, physical assessment, and strength and conditioning preparation [13]. In the Portuguese elite male futsal cohort, sprain/ligament injuries and muscle injuries were the most common injury types, with the groin, thigh, knee, and ankle being the most affected areas [10]. In female futsal, ankle, thigh, knee, and groin injuries are also prominent, with sprains and strains being frequent [14]. The present study aligns with this global pattern in showing a predominance of ankle and knee injuries. However, the proportion of players reporting ankle involvement was especially high, which may indicate a combination of sport-specific demands and local modifiable factors such as surface quality, footwear, limited preventive training, and incomplete rehabilitation. Because injuries were self-reported and not clinically verified, some diagnostic misclassification is possible; for example, players may label different ankle injuries as “sprains,” or confuse muscle cramps, contusions, and strains. This limitation should temper interpretation of the exact distribution of injury types.

The finding that most injuries occurred during matches is consistent with prospective futsal and football evidence. Lopes et al. found that injury incidence in elite male futsal was much higher during matches than training [10]. Similar patterns are reported in football, where systematic review evidence shows that match injury rates are several times higher than training injury rates in both professional and amateur male players [15]. This likely reflects higher intensity, fatigue, tactical pressure, unanticipated movements, and greater player-to-player contact during competition. In the present study, most injuries were attributed to contact with opponents. This is plausible because futsal involves rapid acceleration, deceleration, shielding, tackling, and close-space duels. However, the study relied on player recall rather than video analysis or clinician-recorded injury mechanisms. Therefore, mechanisms such as “contact,” “body rotation,” or “incorrect landing” should be viewed as perceived mechanisms rather than confirmed biomechanical causes. This distinction is important because football video-analysis studies show that many serious knee injuries involve indirect contact or non-contact mechanisms even when players perceive an external perturbation [16, 17]. Future research in Afghanistan should therefore distinguish direct contact, indirect contact, and non-contact injuries more precisely.

A particularly important contextual finding was the reported contribution of unsuitable venues. More than one-quarter of players attributed injuries to unsuitable venues, and only 18.3% reported that venues were consistently suitable. This finding has strong practical importance in a low-resource sports setting. International futsal literature recognizes playing facilities and equipment as relevant prevention targets [13], but in many high-income or professional settings, court quality, lighting, space, first aid availability, and medical coverage are more standardized. In Herat, venue conditions may vary widely, making infrastructure a central component of injury prevention.

In adjusted analysis, players who reported that venues were only sometimes suitable had higher odds of injury history compared with those reporting consistently suitable venues. This finding is more consistent with the descriptive concern that inconsistent venue quality may contribute to injury burden. However, it should still not be interpreted as causal evidence because the study was cross-sectional, venue suitability was self-reported, and the model was affected by sparse non-injury events and wide confidence intervals. More likely explanations include residual confounding, differences in cumulative exposure, variation in interpretation of the venue question, and model instability. The more defensible implication is descriptive and practical: many players perceive venue quality as a contributor to injury, and systematic venue assessment should be included in future prospective surveillance.

The limited awareness and use of FIFA 11 + is another actionable finding. In this sample, 38.9% did not use FIFA 11 + and 23.6% were unaware of it. Although FIFA 11 + was developed for football rather than specifically for futsal, its focus on neuromuscular control, strength, balance, landing mechanics, and movement quality is relevant to lower-limb injury prevention in futsal. Multiple reviews and meta-analyses support the injury-preventive effect of FIFA 11 + or similar neuromuscular warm-up programmes in football. Barengo et al. reported that FIFA 11 + implementation was associated with injury reductions of approximately 30% to 70% in amateur football settings [18]. Sadigursky et al. found a 30% reduction in injury risk in a meta-analysis of randomized clinical trials [19]. Thorborg et al. reported that FIFA 11 + reduced overall football injuries by approximately 39%, whereas the older FIFA 11 programme did not show the same preventive effect [20]. More recent evidence also suggests that neuromuscular training effectiveness depends strongly on adherence and coach education [21]. The implication for Herat is therefore practical: simple coach-led warm-up programmes may be among the most feasible low-cost interventions, but implementation must be adapted to local language, facilities, coaching routines, and player adherence. Because this study did not measure quality, frequency, or fidelity of FIFA 11 + use, it cannot determine whether the programme protected against injury in this population.

The study also identified several lifestyle and recovery concerns. Energy drink consumption was extremely common, reported by 90.8% of players. This is much higher than levels reported in many adolescent and young adult populations internationally. For example, a study of adolescent athletes found that 69% consumed energy drinks, with 17% using them daily or one to three times weekly [22]. Systematic review evidence indicates that energy drink use among young people is associated with insomnia, headaches, hyperactivity, risk behaviours, and other adverse outcomes, although most evidence is observational and cannot establish causality [23]. A meta-analysis of adverse events found that energy drink consumption increased the odds of insomnia and jitteriness/activeness compared with controls [24]. In the present study, energy drink use should not be presented as a proven cause of futsal injury because the design does not establish temporality and the analysis did not demonstrate a causal pathway. However, the high prevalence is still important. In athletes, stimulant use may mask fatigue, disrupt sleep, replace appropriate nutrition and hydration, and create cardiovascular or neuropsychological concerns. Therefore, education on energy drinks should be included within broader player health promotion, especially because more than half of players reported sleeping less than eight hours before a match.

Sleep and nutrition findings also deserve cautious interpretation. In this study, many players reported irregular sleep or less than eight hours before matches, while use of structured diets and supplements was rare. International evidence suggests that sleep and nutrition can influence injury risk, although the relationship is complex and often confounded by training load, stress, and recovery. Von Rosen et al. found that adolescent elite athletes sleeping more than eight hours on weekdays had lower odds of injury, and adequate nutrition was also associated with lower injury odds [25]. Another prospective study using a biopsychosocial perspective found that increased training load and intensity combined with decreased sleep volume produced a higher injury risk [26]. The present study did not prospectively measure sleep, diet, training load, or injury onset, so it cannot determine whether poor sleep or nutrition preceded injury. Nevertheless, the descriptive results identify modifiable recovery behaviours that are suitable targets for education, especially in a setting where formal sports nutrition support may be limited.

The sociodemographic associations require particularly careful discussion. In bivariate analysis, age, marital status, economic status, and employment status were associated with injury history. However, these factors were measured at the time of survey, whereas injuries could have occurred at any earlier point in a player’s futsal career. Therefore, they should not be interpreted as causal determinants. The age findings also illustrate why caution is needed. Bivariate results suggested that injury prevalence increased with age, which is intuitive because older players have had more cumulative playing exposure. In the adjusted analysis, players aged 25–34 years had higher odds of injury history compared with those aged 14–20 years, although the confidence interval was wide. This direction is plausible because older players may have had greater cumulative playing exposure and therefore more opportunity to experience at least one lifetime futsal-related injury. However, the result should still be interpreted cautiously because injury history was measured retrospectively, exact exposure hours were not measured, and the small number of non-injured participants may have produced unstable estimates. The appropriate interpretation is that age is associated with reported injury history, but this study cannot determine the direction, magnitude, or causal nature of that association. The absence of exposure-duration data limits interpretation of age-related findings because older players may have had greater cumulative opportunity to experience injury.

Similarly, the marital status result should not be overinterpreted. Single players reported higher injury prevalence than married players in bivariate analysis, but any explanation involving risk-taking, family responsibility, or behavioural differences would be speculative without direct evidence. Marital status may simply be acting as a proxy for age, cumulative exposure, social role, training opportunity, or reporting behaviour. Because marital status at survey may not match marital status at the time of injury, the result should be framed as a descriptive association rather than a meaningful independent risk factor. The discussion should explicitly avoid claims that being single or married causes injury.

Economic status also requires a nuanced interpretation. In bivariate analysis, players with good or very good economic status had the highest injury prevalence, and the adjusted analysis also showed higher odds of injury history among players with good/very good economic status compared with those reporting poor/very poor economic status. This finding should not be interpreted as evidence that better economic status directly increases injury risk. A more plausible explanation is that players with better economic status may have greater cumulative exposure through more frequent participation, longer playing careers, better access to organized clubs, or greater likelihood of reporting previous injuries. At the same time, lower economic status may still influence access to safe environments, protective equipment, healthcare, and rehabilitation. Future studies should measure exposure hours, footwear, court type, treatment delay, rehabilitation completion, and recurrent injury to clarify these pathways.

The high use of specialists, alongside frequent use of local/traditional healers and home remedies, is another important context-specific result. Most injured players reported seeking care from a specialist, which is encouraging. However, 31.4% reported treatment from local healers and 15.3% used home remedies. This should not be presented dismissively; traditional care pathways may reflect cultural trust, affordability, availability, family influence, and limited access to sports medicine services. Evidence from other low-resource settings suggests that injured individuals may seek traditional healers for reasons related to access, beliefs, perceived effectiveness, and health-system barriers [27]. The main implication is that injury management strategies in Herat should be culturally sensitive. Rather than simply discouraging traditional care, clubs and health authorities could promote early recognition of red flags, timely referral for suspected fractures or ligament injuries, and safe return-to-play guidance. Collaboration with community health actors may be more realistic than relying only on specialist-based models.

The main statistical implication of this study is that the injury burden is clear, but the correlates are exploratory. Because the outcome was very common, odds ratios may overstate associations compared with risk ratios. The small number of non-injured players also reduces model stability and produces wide confidence intervals. In addition, multiple bivariate tests increase the likelihood of chance findings. Therefore, the strongest conclusions should focus on descriptive injury patterns and modifiable system-level gaps: lower-limb injury predominance, match-related injuries, contact mechanisms, limited FIFA 11 + awareness, perceived venue problems, high energy drink use, suboptimal sleep, and mixed treatment pathways. The regression results are best framed as hypothesis-generating signals for future prospective research rather than as definitive risk prediction.

The adjusted regression findings should be interpreted with caution. Although logistic regression was used to explore adjusted associations, the high prevalence of injury and the small number of non-injured participants limited model stability. Wide confidence intervals suggest imprecision, and some estimates may reflect sparse-data bias or residual confounding. Therefore, the main value of this study lies in its descriptive epidemiology, including the burden, anatomical distribution, timing, mechanisms, and contextual features of futsal injuries in Herat.

Measurement bias is also important. Injury status, injury type, anatomical location, mechanism, treatment, sleep, diet, energy drink use, and training characteristics were self-reported. This may introduce recall bias, especially because the outcome covered the entire playing career rather than a defined recent period. More severe injuries may be remembered better than minor injuries, while common terms such as “sprain,” “tear,” “cramp,” and “contusion” may be interpreted differently by players. Social desirability bias may also affect reporting of diet, tobacco, sleep, use of preventive programmes, or treatment choices. Additionally, currently active players were surveyed; players who had stopped playing because of severe injuries may have been missed, while players absent due to current injury may also have been underrepresented. These issues mean that the prevalence estimate should be interpreted as the burden of recalled injury among accessible active league players, not as the true incidence of futsal injury in Herat.

Overall, the findings suggest that futsal injury prevention in Herat should be multi-component and locally adapted. At the player and coach level, implementation of a structured neuromuscular warm-up such as FIFA 11 + or a futsal-adapted equivalent is justified by international evidence and by the local predominance of ankle and knee injuries. At the club level, simple injury logs, basic first-aid readiness, return-to-play guidance, and coach education could be introduced with minimal cost. At the infrastructure level, routine inspection of playing surfaces, lighting, crowding, and venue safety should be prioritized because players frequently identified unsuitable venues as a contributor to injury. At the health-system level, referral links between clubs, physicians, physiotherapists, and culturally trusted care providers could improve injury diagnosis and rehabilitation. Finally, future research should move from lifetime self-report toward prospective injury surveillance using exposure hours, standardized definitions, clinical verification where possible, and repeated measurement of time-varying factors such as training load, sleep, nutrition, venue, footwear, and preventive programme adherence. The injury profile observed among male futsal players in Herat shares important similarities with international futsal literature, particularly the predominance of lower-limb injuries and the concentration of injuries during matches. However, the setting also presents distinct prevention challenges, including limited FIFA 11 + awareness, perceived venue inadequacy, widespread energy drink consumption, irregular sleep, and reliance on both biomedical and traditional treatment pathways. These context-specific findings are the most important contribution of the study. They support the need for feasible, culturally appropriate, and infrastructure-aware injury prevention rather than simply importing prevention models from professional high-resource sport settings.

Strengths and limitations

This study has several strengths. It is the first study, to our knowledge, to describe futsal-related injuries among male league players in Herat, Afghanistan, an under-studied low-resource and post-conflict setting. The study included players from two competitive tiers and collected multidimensional information on sociodemographic characteristics, anthropometry, lifestyle, nutrition, sleep, training, prevention-program awareness, injury characteristics, and treatment patterns. These data provide an initial evidence base for future prospective injury surveillance and locally tailored prevention strategies.

However, several limitations must be considered. First, the cross-sectional design prevents temporal and causal inference. Injury history was assessed over the player’s futsal career, whereas exposures such as marital status, economic status, training habits, and FIFA 11 + use were measured at the time of survey. Therefore, these variables may not reflect the player’s status at the time the injury occurred. Second, injury history was self-reported and may be affected by recall bias, particularly for minor or distant injuries. Third, injury diagnosis, type, severity, and anatomical location were not clinically verified by a physician or physiotherapist, which may have introduced misclassification. Fourth, the use of convenience-based recruitment and an attempted census of accessible players may have introduced selection bias; players absent because of severe injury may have been missed. Fifth, residual confounding is possible because important variables such as exact player-hours of exposure, previous injury timing, rehabilitation quality, footwear, court surface quality, and objective training load were not measured. Sixth, the adjusted regression models should be interpreted cautiously because the injury outcome was highly prevalent and the number of non-injured participants was small, resulting in wide confidence intervals. Seventh, This study did not measure player-hours of match or training exposure, total career duration, or cumulative years of futsal participation. Therefore, players with longer exposure to futsal may have had more opportunity to sustain and report an injury. This is particularly relevant because the outcome was lifetime injury history rather than injury incidence during a defined follow-up period. Future studies should use prospective injury surveillance and calculate injury incidence per 1,000 h of match and training exposure. Finally, although BMI was calculated, direct body-composition measures were not collected; therefore, BMI should not be interpreted as a precise measure of adiposity in this athletic population.

Policy significance

The findings have practical implications for futsal clubs, coaches, local sports authorities, and healthcare providers in Herat. The high self-reported burden of injury suggests a need for basic, feasible injury-prevention and management strategies rather than resource-intensive programmes alone. In the short term, low-cost actions such as coach-led warm-up education, simple injury-recording forms, player education in local languages, and routine checks of playing surfaces may be achievable. In the medium term, clubs and local sports authorities could develop referral links with physiotherapists and physicians for injury assessment and return-to-play guidance. In the long term, a formal injury surveillance system could help monitor injury incidence, evaluate prevention efforts, and guide resource allocation. Because the observed associations are exploratory, policy decisions should focus primarily on the documented injury burden and modifiable prevention gaps rather than assuming causal effects of sociodemographic variables.

Recommendations

Based on the findings, a staged and resource-sensitive approach is recommended.

Short-term priorities

First, clubs should provide basic player and coach education on warm-up routines, safe landing and cutting techniques, hydration, sleep, nutrition, early injury reporting, and risks of premature return to play. Second, coaches should be trained to implement a structured neuromuscular warm-up, such as FIFA 11 + or a locally adapted equivalent, before training and matches. Third, clubs should use simple injury logs to record injury type, timing, mechanism, and whether medical care was obtained.

Medium-term priorities

Local futsal authorities should encourage routine inspection of playing venues, with attention to floor condition, lighting, crowding, and availability of basic first aid. Clubs should also establish referral pathways with local physicians and physiotherapists to support appropriate diagnosis, rehabilitation, and return-to-play decisions.

Long-term priorities

A prospective injury surveillance system should be developed across futsal clubs in Herat to measure injury incidence per player-hours of exposure and evaluate the effectiveness of prevention strategies. Future programmes should combine structured warm-up, safer facilities, protective-equipment access, rehabilitation support, and culturally appropriate education rather than relying on a single intervention.

Conclusion

This cross-sectional study provides the first description of self-reported futsal-related injuries among active male Premier League and First Division players in Herat, Afghanistan. A high proportion of players reported at least one futsal-related injury during their playing career, with ankle and knee injuries being most common and most injuries occurring during matches. The adjusted analyses identified associations with older age, good/very good economic status, evening training, and venues reported as only sometimes suitable; however, these findings should be interpreted cautiously because of the lifetime recall period, cross-sectional design, self-reported injury assessment, limited number of non-injured participants, wide confidence intervals, and potential residual confounding. The findings support the need for feasible injury-prevention education, safer playing environments, improved access to appropriate care, and prospective injury surveillance to better estimate injury incidence and identify modifiable risk factors in this setting.

Abbreviations

aOR

Adjusted odds ratio

BMI

Body mass index

CI

Confidence interval

FIFA

Fédération Internationale de Football Association

IRB

Institutional Review Board

OR

Odds ratio

SPSS

Statistical Package for the Social Sciences

Authors' contributions

MS, MM, AR, FA, MSS, and NAS conceptualized the study, contributed to manuscript drafting, reviewed and edited the manuscript, and approved the final version. MS and MM supervised the study process. NAS contributed to statistical and methodological oversight. All authors read and approved the final manuscript.

Funding

This research received no external funding.

Data availability

The raw data analyzed during the current study are not publicly available because of participant confidentiality. The data are available from the corresponding author, Mohammad Masudi, upon reasonable request (email: mhmasoudy313@gmail.com).

Declarations

Ethics approval and consent to participate

The study was approved by the Institutional Review Board of Ghalib University on November 4, 2023 (approval code: Afg-Gh.U.H-R.E.C.2023-0038). The study was conducted in accordance with the Declaration of Helsinki and the ethical principles for research involving human participants. Written informed consent to participate was obtained from all participants before data collection. For participants younger than 16 years, written informed consent to participate was obtained from a parent or legal guardian. Participation was voluntary, and the confidentiality and privacy of participants were maintained throughout the study.

Consent for publication

Not Applicable.

Competing interests

The authors declare no competing interests.